Unnamed: 0
int64 0
6.64k
| title
stringlengths 4
125
| enrolled
stringlengths 5
27
| rating
stringclasses 22
values | num_reviews
float64 1
229k
⌀ | Instructor
stringlengths 2
66
⌀ | Organization
stringclasses 298
values | Skills
stringlengths 2
462
| Description
stringlengths 123
32.8k
⌀ | Modules/Courses
stringclasses 43
values | Level
stringclasses 3
values | Schedule
stringclasses 130
values | URL
stringlengths 33
128
| Satisfaction Rate
stringclasses 29
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
900 |
Machine Learning Rock Star – the End-to-End Practice
Specialization
|
10,100
|
4.8
| 144 |
Eric Siegel
|
SAS
|
['Predictive Analytics', 'Ethics Of Artificial Intelligence', 'Artificial Intelligence (AI)', 'Data Science', 'Machine Learning', 'Machine learning strategy and leadership', 'Predictive Analytics', 'Ethics Of Artificial Intelligence', 'Artificial Intelligence (AI)', 'Data Science', 'Machine Learning', 'Machine learning strategy and leadership']
|
Machine learning reinvents industries and runs the world.Harvard Business Reviewcalls it “the most important general-purpose technology of our era.” But while there are so many how-to courses for hands-on techies, there are practically none that also servethe business leadership of machine learning– a striking omission, since success with machine learning relies on a very particular project leadership practice just as much as it relies on adept number crunching. By filling that gap, this course empowers you to generate value with ML. It delivers the end-to-end expertise you need, coveringboth the core technology and the business-side practice. Why cover both sides? Because both sides need to learn both sides! This includes everyone leading or participating in the deployment of ML. NO HANDS-ON.Rather than a hands-on training, this specialization serves both business leaders and burgeoning data scientists with expansive, holistic coverage. BUT TECHNICAL LEARNERS SHOULD TAKE ANOTHER LOOK.Before jumping straight into the hands-on, as quants are inclined to do, consider one thing: This curriculum provides complementary know-how that all great techies also need to master. WHAT YOU'LL LEARN.How ML works, how to report on its ROI and predictive performance, best practices to lead an ML project, technical tips and tricks, how to avoid the major pitfalls, whether true AI is coming or is just a myth, and the risks to social justice that stem from ML. Applied Learning Project Problem-solving challenges: Form an elevator pitch, build a predictive model by hand in Excel or Google Sheets to visualize how it improves, and more (no exercises involve the use of ML software). This specialization includes several illuminating software demos of ML in action using SAS products. However, the curriculum is vendor-neutral and universally-applicable. The learnings apply, regardless of which ML software you end up choosing to work with. Brought to you by a veteran industry leader who won teaching awards when he was a professor at Columbia University, this specialization stands out as one of the most thorough, engaging, and surprisingly accessible on the subject of ML. These three courses are also a good fit for college students, or for those planning for or currently enrolled in an MBA program. The breadth and depth of this specialization is equivalent to one full-semester MBA or graduate-level course. Participate in the deployment of machine learning Identify potential machine learning deployments that will generate value for your organization Report on the predictive performance of machine learning and the profit it generates Understand the potential of machine learning and avoid the false promises of “artificial intelligence” Apply ML: Identify opportunities where machine learning can improve marketing, sales, financial credit scoring, insurance, fraud detection, and more Plan ML: Determine the way machine learning will be operationally integrated and deployed, and the staffing and data requirements to get there Greenlight ML: Forecast the effectiveness of a machine learning project and then internally sell it, gaining buy-in from your colleagues Lead ML: Manage a machine learning project, from the generation of predictive models to their launch Participate in the application of machine learning, helping select between and evaluate technical approaches Interpret a predictive model for a manager or executive, explaining how it works and how well it predicts Circumvent the most common technical pitfalls of machine learning Screen a predictive model for bias against protected classes – aka AI ethics
|
3 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/machine-learning-for-everyone
| null |
901 |
Interprofessional Healthcare Informatics
|
32,246
|
4.5
| 311 |
Karen A. Monsen, PhD, RN, FAMIA, FNAP, FAAN
|
University of Minnesota
|
['Graph Theory', 'Health Informatics', 'Data Virtualization', 'Data Visualization', 'Information Theory']
|
Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education. We will be incorporating technology-enabled educational innovations to bring the subject matter to life. Over the 10 modules, we will create a vital online learning community and a working healthcare informatics network. We will explore perspectives of clinicians like dentists, physical therapists, nurses, and physicians in all sorts of practice settings worldwide. Emerging technologies, telehealth, gaming, simulations, and eScience are just some of the topics that we will consider.
Throughout the course, we’ll focus on creativity, controversy, and collaboration - as we collectively imagine and create the future within the rapidly evolving healthcare informatics milieu. All healthcare professionals and IT geeks are welcome! 1 video2 readings Week 1 begins! This week, we explore and apply theories of healthcare informatics to professional practice. By the end of this week, you will be able to: describe informatics theory, analyze informatics theory related to practice and analyze health topics of interest to healthcare. 2 videos1 reading This module explores and applies standardized terminologies to professional practice. By the end of this module, learners will be able to: analyze the transformation of data to information to knowledge and explore and apply standardized terminologies to professional practice. 3 videos1 reading1 assignment This module links EHR use to evidence-based practice. By the end of this module, learners will be able to: identify the benefits and goals of an electronic health record and analyze evidence-based practice within the context of the electronic health record. 2 videos1 reading1 assignment Week 5 begins! This week we examine informatics in relationship to new technologies in healthcare. Telehealth and technology are creating new ways to link people, and care, and health information. By the end of this week, you will be able to: examine applications of telehealth technologies and describe methods of engaging consumers in using health information technologies. 2 videos1 reading1 assignment This module examines informatics in relationship to new technologies in healthcare. By the end of this module, learners will be able to: examine applications of telehealth technologies and describe methods of engaging consumers in using health information technologies. 3 videos1 reading1 assignment This module relates informatics to community and population health. By the end of this module, learners will be able to: relate informatics to community and population health and analyze applications of geospatial information systems and health. 1 video1 reading1 assignment This module describes applications of gaming, simulation, and virtual reality tools in healthcare. By the end of this module, learners will be able to: analyze informatics and gaming in relationship to health and healthcare and describe use of simulations and informatics to improve healthcare quality. 3 videos1 reading1 assignment This module explores ethical issues related to healthcare informatics in the interprofessional context. By the end of this module, learners will be able to: explore ethical issues related to healthcare informatics in the interprofessional context and analyze security and privacy challenges related to healthcare informatics. 1 video1 reading1 assignment This module explores interprofessional aspects of healthcare data exchange and interoperability. By the end of this module, learners will be able to: describe information exchange and interoperability and analyze interprofessional aspects of information exchange and interoperability in healthcare. 4 videos1 reading1 assignment This module explores the contribution of healthcare informatics to the foundation of knowledge in healthcare. By the end of this module, learners will be able to: analyze implications of Big Data for healthcare research and synthesize insights related to interprofessional healthcare informatics. 4 videos1 reading1 assignment
|
11 modules
| null |
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/health-informatics-professional
|
95%
|
902 |
Healthcare Data Quality and Governance
|
9,264
|
4.6
| 100 |
Doug Berman
|
University of California, Davis
|
[]
|
Career prospects are bright for those qualified to work with healthcare data or as Health Information Management (HIM) professionals. Perhaps you work in data analytics but are considering a move into healthcare, or you work in healthcare but are considering a transition into a new role. In either case, Healthcare Data Quality and Governance will provide insight into how valuable data assets are protected to maintain data quality. This serves care providers, patients, doctors, clinicians, and those who carry out the business of improving health outcomes. "Big Data" makes headlines, but that data must be managed to maintain quality. High-quality data is one of the most valuable assets gathered and used by any business. This holds greater significance in healthcare where the maintenance and governance of data quality directly impact people’s lives. This course will explain how data quality is improved and maintained. You’ll learn why data quality matters, then see how healthcare professionals monitor, manage and improve data quality. You’ll see how human and computerized systems interact to sustain data quality through data governance. You’ll discover how to measure data quality with metadata, tracking data provenance, validating and verifying data, along with a communication framework commonly used in healthcare settings.
This knowledge matters because high-quality data will be transformed into valuable insights that can save lives, reduce costs, to improve healthcare and make it more accessible and affordable. You will make yourself more of an asset in the healthcare field by what you gain from this course. In this module, you will be able to define data quality and what drives it. You'll be able to recall and describe four key aspects of data quality. You'll be able to explain why data quality is important for operations, for patient care, and for the finances of healthcare providers. You'll be able to discuss how data may change over time, and how finding those changes allows us to recognize and work with the issues the changes cause. You will be able to explain why requirements for data quality depend on how we intend to use that data and understand four levels of quality that may be applied for different kinds of analysis. You will also be able to discuss how all of this supports our ability to do our best work in the best ways possible. 6 videos2 readings1 assignment2 discussion prompts This module focuses on measuring data quality. After this module, you will be able to describe metadata, list what metadata may include, give some examples of metadata and recall some of its uses as it relates to measuring data quality. We will describe data provenance to explains how knowing the origin of a data set can help data analysts determine if a data set is suitable for a particular use. We’ll also describe 5 components of data quality you can recall and use when evaluating data. You will also learn to be able to distinguish between data verification and validation, recalling 4 applicable data validation methods and 3 concepts useful to validate data. In addition to your video lessons, you will read and discuss a scholarly article on Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. We wrap up the module with a framework abbreviated as S-B-A-R that is often used in healthcare team situations to communicate about issues that must be solved. 7 videos1 reading1 assignment3 discussion prompts In this module, we focus on monitoring, managing, and improving data quality. You will be able to explain how to monitor data on a day-to-day basis to see that it remains consistent. You will explain how measures can help us monitor the patient health and the quality of care they receive over time. Also, you will be able to discuss establishing the culture of quality throughout the data lifecycle and improving data quality from the baseline by posing questions to determine a baseline of data quality. You will be able to manage data quality through expected and unexpected changes, along with tracking monitoring strategies along the data pipeline. After this module, you will be able to identify and fix common deficiencies in the data and implement change control systems as a monitoring tool. You’ll also recall several best practices you can apply on the job to monitor data quality in the healthcare field. 5 videos1 assignment1 discussion prompt IIn this module, we focus on sustaining quality through data governance. We will define data governance and consider why it matters in healthcare. You will discuss who makes up data governance committees, how these committees function relative to data analysts and describe how stakeholders work together to ensure data quality. You’ll be able to describe how high-quality data is a valuable asset for any business. You will also define data governance systems. You will recall several ways data can be repurposed and explain how data governance maintains data quality as it is repurposed for a use other than that for which it was originally gathered. In addition to your video lessons, you will read and discuss the article, Big Data, Bigger Outcomes and practice applying some of these important concepts. 6 videos3 readings1 assignment1 peer review1 discussion prompt
|
4 modules
|
Intermediate level
|
11 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/healthcare-data-quality-governance
| null |
903 |
Deploying Machine Learning Models
|
10,423
|
3.5
| 51 |
Ilkay Altintas
|
University of California San Diego
|
['Python Programming', 'Big Data Products', 'Recommender Systems']
|
In this course we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g. to predict ratings, or generate lists of related products), and you should understand the tools and techniques required to deploy such a working system on real-world, large-scale datasets. This course is the final course in the Python Data Products for Predictive Analytics Specialization, building on the previous three courses (Basic Data Processing and Visualization, Design Thinking and Predictive Analytics for Data Products, and Meaningful Predictive Modeling). At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization. Welcome to the first week of Deploying Machine Learning Models! We will go over the syllabus, download all course materials, and get your system up and running for the course. We will also introduce the basics of recommender systems and differentiate it from other types of machine learning 5 videos3 readings3 assignments2 discussion prompts This week, we will learn how to implement a similarity-based recommender, returning predictions similar to an user's given item. We will cover how to optimize these models based on gradient descent and Jaccard similarity. 4 videos3 assignments This week, we will learn about Python web server frameworks and the overall structure of interactive Python data applications. We will also cover some tips for best practices on deploying and monitoring your applications. 3 videos1 reading2 assignments For this final project, you will build a recommender system of your own. Find a dataset, clean it, and create a predictive system from the dataset. This will help prepare you for the upcoming capstone, where you will harness your skills from all courses of this specialization into one single project! 2 readings1 peer review1 discussion prompt Time to put all your hard work to the test! This capstone project consists of four components, each drawing from a separate course in this specialization. It's time to show off everything you've learned from this specialization. 1 video1 reading1 peer review1 discussion prompt
|
5 modules
| null |
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/deploying-machine-learning-models
| null |
904 |
Oracle Autonomous Database Professional Workshop
|
5,476
|
4.6
| 39 |
Roy Swonger
|
Oracle
|
['Deploying an Autonomous Database', 'Identify Migration Options and Considerations', 'Planning and implementing an Autonomous Database', 'Creating an Autonomous Database']
|
Welcome to the course Oracle Autonomous Database Administration. This course helps DBAs to deploy and administer Autonomous databases, and prepares them for the Oracle Autonomous Database Cloud Specialist Certification. In this module we introduce you to the core concepts of Autonomous Database and the different ways to provision an ADB 22 videos4 assignments In this module we will show you how to manage and monitor an autonomous database. We will cover concepts of auto scaling, automatic indexing, and show how you can connect to an autonomous database from SQL developer. In this module you will also learn to configure an Autonomous Data Guard for disaster recovery. 15 videos2 assignments In this module you will learn how to create applications on Autonomous Database using SQL, APEX, and Oracle Machine Learning.
You will also learn to make use of Spatial Studio, and Graph Studion. This module also covers how to migrate data to an Autonomous Database. 21 videos4 assignments This module prepares you for the Oracle Autonomous Database Cloud Professional Exam by reviewing key exam topics, providing sample questions, and sharing test-taking strategies. 3 videos
|
4 modules
|
Intermediate level
|
7 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/oracle-autonomous-database-professional-workshop
| null |
905 |
Anatomy & Physiology: Regulation, Integration, & Control
|
1,574
|
4.9
| 11 |
Laura S. Kabiri
|
Rice University
|
['Anatomical Terminology', 'Physiological Processes', 'Organ Systems', 'Clinical Relevance', 'Research and Information Literacy']
|
This course continues the systems-based approach to human anatomy and physiology at the organ, organ system, and organism level. Two major body systems related to regulation and integration of information will be explored in detail: the nervous and endocrine systems. Course material will cover both the structure (anatomy) and function (physiology) of each system with direct application to human development and disease. 2 videos3 readings1 plugin 4 videos3 readings1 assignment3 discussion prompts 4 videos3 readings1 assignment1 peer review3 discussion prompts 3 videos2 readings1 assignment1 peer review 1 video1 assignment
|
5 modules
|
Intermediate level
|
9 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/anatomy--physiology-regulation-integration--control
| null |
906 |
Algebra: Elementary to Advanced Specialization
|
24,813
|
4.8
| 594 |
Joseph W. Cutrone, PhD
|
Johns Hopkins University
|
[]
|
This specialization is intended for students looking to solidify their algebra and geometry necessary to be successful in future courses that will require precalculus and calculus. Quantitiative skill and reasoning are presented throughout the course to train students to think logically, reason with data, and make informed decisions. Applied Learning Project Instead of a single large project, there are many smaller applied and algebra problems throughout the modules of the courses. Practice problems with worked solutions are provided throughout the course to prepare students and allow them to be successful. Problems range in difficulty to allow students to be challenged as they apply the knowledge gained from the course. This course is intended for students looking to create a solid algebraic foundation of fundamental mathematical concepts from which to take more advanced courses that use concepts from precalculus, calculus, probability, and statistics. This course will help solidify your computational methods, review algebraic formulas and properties, and apply these concepts model real world situations. This course is for any student who will use algebraic skills in future mathematics courses. Topics include: the real numbers, equalities, inequalities, polynomials, rational expressions and equations, graphs, relations and functions, radicals and exponents, and quadratic equations. After completing this course, students will learn how to successfully apply functions to model different data and real world occurrences. This course reviews the concept of a function and then provide multiple examples of common and uncommon types of functions used in a variety of disciplines. Formulas, domains, ranges, graphs, intercepts, and fundamental behavior are all analyzed using both algebraic and analytic techniques. From this core set of functions, new functions are created by arithmetic operations and function composition. These functions are then applied to solve real world problems. The ability to picture many different types of functions will help students learn how and when to apply these functions, as well as give students the geometric intuition to understand the algebraic techniques. The skills and objectives from this course improve problem solving abilities. This course is the final course in a three part algebra sequence, In this course, students extend their knowledge of more advanced functions, and apply and model them using both algebraic and geometric techniques. This course enables students to make logical deductions and arrive at reasonable conclusions. Such skills are crucial in today's world. Knowing how to analyze quantitative information for the purpose of making decisions, judgments, and predictions is essential for understanding many important social and political issues. Quantitative Skills and Reasoning provides students the skills needed for evaluating such quantitatively-based arguments. This class is important as the mathematical ideas it treats and the mathematical language and symbolic manipulation it uses to express those ideas are essential for students who will progress to calculus, statistics, or data science.
|
3 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/algebra-elementary-to-advanced
| null |
907 |
Children Acquiring Literacy Naturally
|
27,960
|
4.5
| 172 |
Dr. Dominic William Massaro
|
University of California, Santa Cruz
|
[]
|
In this short course you will explore the possibility that children might acquire written language in a way that is similar to how they acquire spoken language—without instruction. You will encounter various aspects of behavioral science and technology that are relevant to this proposition. You will have the opportunity to learn the the perceptual, cognitive, and neurological capacities of children during their first years of life. You will advance your understanding of children and how they learn language. You will also be more attuned to current advances in the technology of human machine interactions, and what these phenomena imply for learning to read at an early age. Universal literacy, differences between spoken and written language, models of perception and processing, and implications of natural acquisition of reading. 12 videos1 reading4 discussion prompts Influences on language learning, iconicity, recognition skills of infants, visual processes in reading, and rapid serial visual processing. 14 videos2 readings4 discussion prompts The nature of reading, reading myths, current approaches to teaching reading, demographics of literacy and illiteracy, and technological innovations. 15 videos1 reading1 peer review3 discussion prompts
|
3 modules
|
Beginner level
| null |
https://www.coursera.org/learn/children-literacy
|
98%
|
908 |
Teaching in University Science Laboratories (Developing Best Practice)
|
11,565
|
4.7
| 123 |
Natasa Brouwer
|
University of Amsterdam
|
[]
|
This course is developed to improve the effectiveness of laboratory classes in higher education. It aims to support teachers to improve their teaching skills for active learning in university science laboratory courses. It will show you how laboratory sessions can differ with respect to their aim and expected learning outcomes, how to engage students for learning and how to cope with their different levels of pre-knowledge and experience and probe their understanding. Last but not least it will show how you could assess students in laboratory courses. This course is developed by ECTN (European Chemistry Thematic Network), Working group Lecturing Qualifications and Innovative Teaching Methods. In this module you will learn about different types of laboratory sessions and get acquainted with strategies that can improve student’s engagement in lab sessions. You will get an introduction about this course as a whole and set your personal goals for it. 1 video8 readings1 peer review4 discussion prompts This module is about qualities needed to be a good laboratory teacher. 1 video7 readings1 peer review4 discussion prompts This module is about the learning theories that can be applied to ensure effective teaching of laboratory work. 2 videos5 readings2 assignments1 peer review1 discussion prompt This module is about giving instruction in a lab session. We present different strategies how to support learning by questioning and how to prevent information overload. 3 videos5 readings1 peer review5 discussion prompts In this module we present the rubric, a tool which can be used for assessing and giving feedback to students on their learning goals. We also consider the concept of constructive alignment of learning outcomes, teaching and learning activities and assessment. 2 videos4 readings2 assignments1 peer review2 discussion prompts In this module we ask you to look back on what you have learned in this online course and to make your own plan about the improvements of the laboratory course in which you teach. 1 reading2 assignments1 discussion prompt This is an additional week for the ones who need it to finish all the assignments and get the cetificate of the course.
Good luck! 1 reading
|
7 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/developing-university-lab-education
|
98%
|
909 |
Feedback Loops: Horizontal Feedback
|
Enrollment number not found
|
Rating not found
| null |
Patrick Barry
|
University of Michigan
|
['Communication', 'Emotional Intelligence', 'Perspective-Taking', 'teamwork']
|
What’s the best way to give and get feedback from a coworker? How about from a classmate, teammate, or friend? These and other horizontal feedback opportunities can sometimes cause a lot of anxiety, jealousy, bitterness, and misinformation. This course will help you avoid those pitfalls and turn peer feedback into a source of mutually beneficial improvement. What are two characteristics of helpful feedback? What form of feedback has been shown to have tremendous positive effects, especially among young people? And why might it be good to put together a "Feedback Board of Directors"? 3 videos9 readings3 assignments1 app item2 discussion prompts Who in your feedback network might be able to help you as a "fellow storyteller"? 3 videos4 readings3 assignments1 app item2 discussion prompts What's the "cost of conformity" and how can we address it? 4 videos2 readings3 assignments1 app item1 discussion prompt How "dense" and "intense" is your feedback network? 4 videos3 readings3 assignments1 app item2 discussion prompts
|
4 modules
|
Beginner level
|
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/horizontal-feedback
| null |
910 |
Robotic Process Automation (RPA) Specialization
|
12,006
|
4.7
| 290 |
UiPath
|
UiPath
|
['Error Handling Approach & Activities', 'Loops in Studio', 'Control Flow Activities', 'Flowcharts and Decision Making', 'Sequences', 'Asset', 'UiPath Orchestrator', 'Orchestrator user interface', 'Queues', 'Error Handling Approach & Activities', 'Loops in Studio', 'Control Flow Activities', 'Flowcharts and Decision Making', 'Sequences', 'Asset', 'UiPath Orchestrator', 'Orchestrator user interface', 'Queues']
|
The Robotic Process Automation (RPA) specialization offers comprehensive knowledge and professional-level skills focused on developing and deploying software robots. It starts with the basic concepts of Robotic Process Automation. It builds on these concepts and introduces key RPA Design and Development strategies and methodologies, specifically in the context of UiPath products. A student undergoing the course shall develop the competence to design and develop automation solutions for business processes. This specialization also prepares you for UiPath Certified Professional - UiRPA exam. Applied Learning Project The practice exercises of the course consists of exercises mapped to the Theory portion. Each exercise will help the student practice and apply the skills learned in the Theory section. At the end of the specialization is an industry-level capstone project which will help the students to assimilate the knowledge and skills learnt and build an end-to-end automation solution for a business process. Robotic Process Automation basic concepts UiPath Studio and its User Interface How to build automation projects in UiPath Studio Variables and Arguments Data Manipulation in Studio Collection Variables in Studio User Interface Automation with Studio Working with different types of Selectors in Studio Recording feature and its appropriate usage in automation projects Types of Loops and Control Flow activities in Studio Flowcharts in Studio Approach and activities for Error Handling in Studio Sequences and Decision-making in Studio Screen Scraping Data Scraping PDF Extraction Workbook, Excel and Email Automation Orchestrator User Interface and Capabilities Assets Queues
|
6 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/roboticprocessautomation
| null |
911 |
Generative AI for Data Visualization and Data Storytelling
|
Enrollment number not found
|
Rating not found
| null |
Dev Ramesh
|
Coursera Instructor Network
|
['Proficient Use of Generative AI for Data Visualization', 'Basic understanding of data analysis and charts', 'Evaluating AI Tools', 'Application of AI in Real-World Scenarios']
|
In today’s data-driven world, harnessing the power of Generative AI to create impactful data visualizations is essential for effective communication and decision-making. This course focuses on utilizing cutting-edge AI tools to transform raw data into dynamic, insightful visual artifacts, enhancing your ability to convey complex information clearly and compellingly. Designed for data analysts, business intelligence professionals, and anyone involved in data storytelling, this course provides practical knowledge and skills to optimize your data visualization processes using AI. You'll explore current and emerging trends in AI-powered visualization platforms, ensuring you stay ahead in the ever-evolving data landscape.
During this course, you'll focus on the following learning objectives:
-Identify how AI tools transform traditional data visualization practices to produce dynamic, insightful presentations.
-Analyze data visualization techniques with LLM-Chat interfaces to enhance understanding and communication of complex information.
-Apply generative AI techniques for data storytelling, utilizing visualization methods to create compelling narratives.
By completing this course, you'll be equipped to:
-Understand and utilize cutting-edge Generative AI tools to create data visualization artifacts.
-Gain practical knowledge on optimizing data visualization processes using AI.
-Explore current and emerging trends in data visualization through AI-powered visualization platforms.
This course is unique because it allows you to convert raw data into intuitive visualizations through various real-world industry examples. Generative AI empowers users to effectively communicate insights and make informed data-driven decisions. Whether you’re new to data visualization or looking to simplify complex information, this course equips you to uncover patterns, trends, and relationships using Generative AI tools.
To succeed in this course, you should have a basic understanding of data analysis and charts, along with a willingness to explore innovative AI-driven solutions for data visualization. Upon the completion of this course, learners will be able to use Generative AI to do data wrangling, automate aspects of data visualization workflows, and create insightful and dynamic data storytelling. 1 video1 reading This lesson provides a comprehensive exploration of how Generative AI revolutionizes the field of data visualization. By the end of this lesson, you will have learned about visualization skills and understood cutting-edge Generative AI tools to create data visualization artifacts. 2 videos1 reading1 assignment In this lesson, you will discover how to leverage LLM-Chat Interfaces for efficient data wrangling and chart creation tasks. By utilizing these tools, you will enhance your data analysis and presentation skills, enabling them to communicate insights effectively. 2 videos1 reading1 assignment In this lesson, you will explore a diverse range of real-world scenarios and applications where AI plays a crucial role in data visualization. Through engaging content, you will discover how to leverage Generative AI tools effectively to create insightful and impactful visualizations that drive informed decision-making. By the end of this lesson, you will have an understanding of the potential of Generative AI in enhancing data visualization across different industries and use cases. 2 videos3 readings2 assignments
|
4 modules
|
Intermediate level
|
2 hours to complete
|
https://www.coursera.org/learn/generative-ai-for-data-visualization-and-data-storytelling
| null |
912 |
HEALTHY URBAN SYSTEMS Specialization
|
Enrollment number not found
|
Rating not found
| null |
Prof. Céline Rozenblat
|
University of Lausanne
|
['Urban Health Systems', 'Scenario Design', 'Multidisciplinary Collaboration', 'Systems Thinking', 'Environmental Health', 'Policy Design and Governance', 'Human Ecology', 'Resilient Governance', 'Complex systems']
|
The MOOC Healthy Urban Systems stresses numerous urban health issues and solutions in a comprehensive introduction on Multidisciplinary Frameworks, Observations & Measures, Concepts & Theories, Modeling Tools, Scenarios Design, and Policies and governance. The up-to-date knowledge is based on various examples, on their implication for the contemporaneous questions, and on the most recent tools and technics of systemic approaches, machine learning, open and FAIR data, participatory, collaborative and action-research. It encourages place-based policies WITH the people and FOR the people in a multi-scale and long-term perspective beyond SDGs’ 2030 and towards the new “Pact for the Future” 2050. 30 international researchers, practitioners and professionals in North and South countries participated to this initiative, that is coordinated and produced by the University of Lausanne – UNIL together with: - the International Science Council program on Urban Health and Wellbeing (ISC – UHWB) - the Institute of Urban Environment (IUE), Chinese Academy of Science in Xiamen, China. - the International Society for Urban Health (ISUH) - the HUE (Healthy Urban Environments) Collaboratory - the World Health Organization (WHO), Department of Environment, Climate Change and Health (HQ/ECH) Applied Learning Project What is unique abouturban health, is the broad understanding of the root causes of health and disease, as described byplanetary boundaries and social determinants of health;how they affect health of citizens and of the city itself, and how urban responses can build synergies and contribute to health, wellbeing and equity as well as ensure that the planet carrying capacity is preserved. Urban health responds both to the ecological boundaries and to the social foundations as illustrated in the Doughnut Economics image by Kate Raworth. Address urban health through complex multidisciplinary approaches Use multidimensional and multiscale concepts, methods and ecosystem frameworks Mobilize and support all players directly or indirectly involved in urban health Theories of complexity Different Methods of Modelling: individual (ABM)aggregated (Dynamic systems) Practice of Holistic Systems Modeling This MOOC is the third part (out of three parts) of the whole MOOC on Healthy Urban Systems. This PART III is very recommended (but not obliged) to take after the PART I and PART II. Once you understood the main concepts and visions of Urban Health, and the best practices of observation in PART I, the theories and models in PART II, you are better prepared to take this PART III on Design and policies. This PART III lasts 4 weeks, comprising two modules of 2 weeks each. The number of credits is 2 ECTS. To obtain these credits, you should achieve all the statements required each week. The final elaboration of a policy design and Health Impact assessment on your proper urban health question, will be specifically evaluated.
|
3 course series
|
Beginner level
|
3 months (at 3 hours a week)
|
https://www.coursera.org/specializations/urban-health-systems
| null |
913 |
FPGA Architecture Based System for Industrial Application
|
Enrollment number not found
|
Rating not found
| null |
Subject Matter Expert
|
L&T EduTech
|
['Real-time Applications and Automation with FPGA', 'IoT Integration with FPGA', 'FPGA Architecture and Design', 'Digital Communication Protocols (RS232, I2C, SPI) with FPGA']
|
The course "FPGA Architecture Based System for Industrial Application Using Vivado" is a comprehensive program that focuses on the design and implementation of FPGA-based VLSI systems for industrial applications. Participants will gain practical knowledge and hands-on experience in utilizing Xilinx Vivado software with Artix 7 FPGA boards to develop digital arithmetics, integrate sensors and motors, implement communication protocols, and create IoT applications. By the end of this course, you will be able to:
• Understand the architecture and features of Artix 7 FPGA boards.
• Install and utilize Xilinx Vivado software for FPGA projects.
• Design and implement digital arithmetics including LEDs, adders, buzzer, and pushbuttons using VHDL on FPGA boards.
• Integrate sensors such as accelerometers, gesture recognition sensors, and ultrasonic sensors with FPGAs.
• Interface motors like stepper motors and DC motors with FPGA kits.
• Implement communication protocols including RS232, I2C, and SPI for data exchange.
• Develop IoT applications for remote monitoring and control using FPGA technology.
• Analyze RTL schematics and configure constraint files for FPGA-based designs.
• Validate hardware logic and functionality through simulation and real-time implementation.
• Demonstrate proficiency in designing complex VLSI systems for industrial use cases. This immersive module is meticulously designed to introduce participants to the world of VHDL programming, focusing on its application to FPGA (Field Programmable Gate Array) design using the Artix 7 FPGA board and Xilinx Vivado software. Beginning with an overview of the Artix 7 FPGA board and the significance of Xilinx Vivado in FPGA projects, the module leads learners through the practical aspects of setting up and simulating basic digital logic circuits. Participants will gain hands-on experience in creating projects from scratch, writing VHDL code for various digital functions, and implementing these designs on the FPGA board. Key concepts such as LED control, push button input handling, and more advanced digital circuits like adders and multipliers will be explored. Through step-by-step guidance, this module aims to equip learners with the knowledge and skills to efficiently develop their FPGA projects, from conceptual VHDL coding to physical implementation and real-time testing on the Artix 7 FPGA board. 46 videos3 readings1 assignment This module offers a comprehensive journey through the design and implementation of embedded components and communication protocols on FPGA using Xilinx Vivado. It starts with the basics of sound generation using buzzers controlled by FPGA, extending to sophisticated digital displays and serial communication protocols. Students will engage in hands-on projects that include interfacing with 7-segment displays and LCDs, and implementing serial communication protocols such as RS232, I2C, and SPI. Each section includes developing VHDL code, configuring constraint files for precise hardware interaction, and analyzing RTL schematics for a deeper understanding of the underlying hardware logic. The module culminates with real-world implementation on the Artix 7 FPGA development board, ensuring students can apply theoretical knowledge to tangible FPGA projects. 27 videos1 assignment This module delves into the integration of sensors and motors with FPGA using Xilinx Vivado, focusing on industrial applications. Participants will explore various sensors including accelerometers, gesture recognition sensors, capacitive touch sensors, ultrasonic sensors, as well as the principles and interfacing of motors like stepper motors and DC motors. The module covers topics such as sensor basics, VHDL code design, pin configurations, and simulation techniques using Vivado. Additionally, it introduces IoT concepts and VGA interfaces for remote monitoring and control of industrial systems, providing a comprehensive understanding of sensor-motor integration in FPGA-based VLSI design. 50 videos1 assignment
|
3 modules
|
Intermediate level
|
12 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/fpga-architecture-based-system-for-industrial-application-using-vivado
| null |
914 |
Plant Bioinformatic Methods Specialization
|
16,824
|
4.8
| 755 |
Nicholas James Provart
|
University of Toronto
|
['Genetic Analysis', 'Bioinformatics Analysis', 'Evolution', 'Comparative Genomics', 'Genetic Analysis', 'Bioinformatics Analysis', 'Evolution', 'Comparative Genomics']
|
The past 15 years have been exciting ones in plant biology. Hundreds of plant genomes have been sequenced, RNA-seq has enabled transcriptome-wide expression profiling, and a proliferation of "-seq"-based methods has permitted protein-protein and protein-DNA interactions to be determined cheaply and in a high-throughput manner. These data sets in turn allow us to generate hypotheses at the click of a mouse or tap of a finger.The Plant Bioinformatics Specialization on Coursera introduces core bioinformatic competencies and resources, such as NCBI's Genbank, Blast, multiple sequence alignments, phylogenetics in Bioinformatic Methods I, followed by protein-protein interaction, structural bioinformatics and RNA-seq analysis in Bioinformatic Methods II. In Plant Bioinformatics we cover 33 plant-specific online tools from genome browsers to transcriptomic data mining to promoter/network analyses and others. Last, a Plant Bioinformatics Capstone uses these tools to hypothesize a biological role for a gene of unknown function, summarized in a written lab report.This specialization is useful to any modern plant molecular biologist wanting to get a feeling for the incredible scope of data available to researchers. A small amount of R programming is introduced in Bioinformatic Methods II, but most of the tools are web applications. It is recommended that you have access to a laptop or desktop computer for running these as they may not work as mobile applications on your phone or tablet. Applied Learning Project The Plant Bioinformatics Specialization on Coursera introduces core bioinformatic competencies and resources, such as NCBI's Genbank, Blast, multiple sequence alignments, phylogenetics in Bioinformatic Methods I, followed by protein-protein interaction, structural bioinformatics and RNA-seq analysis in Bioinformatic Methods II. In Plant Bioinformatics we cover 33 plant-specific online tools from genome browsers to transcriptomic data mining to promoter/network analyses and others. Last, a Plant Bioinformatics Capstone uses these tools to hypothesize a biological role for a gene of unknown function, summarized in a written lab report. Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on. Topics covered include multiple sequence alignments, phylogenetics, gene expression data analysis, and protein interaction networks, in two separate parts.
The first part, Bioinformatic Methods I (this one), deals with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics.
The second part, Bioinformatic Methods II, covers motif searching, protein-protein interactions, structural bioinformatics, gene expression data analysis, and cis-element predictions.
This pair of courses is useful to any student considering graduate school in the biological sciences, as well as students considering molecular medicine. Both provide an overview of the many different bioinformatic tools that are out there.
These courses are based on one taught at the University of Toronto to upper-level undergraduates who have some understanding of basic molecular biology. If you're not familiar with this, something like https://learn.saylor.org/course/bio101 might be helpful. No programming is required for this course.
Bioinformatic Methods I is regularly updated, and was completely updated for January 2024. Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on. Topics covered include multiple sequence alignments, phylogenetics, gene expression data analysis, and protein interaction networks, in two separate parts.
The first part, Bioinformatic Methods I, dealt with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics.
This, the second part, Bioinformatic Methods II, will cover motif searching, protein-protein interactions, structural bioinformatics, gene expression data analysis, and cis-element predictions.
This pair of courses is useful to any student considering graduate school in the biological sciences, as well as students considering molecular medicine.
These courses are based on one taught at the University of Toronto to upper-level undergraduates who have some understanding of basic molecular biology. If you're not familiar with this, something like https://learn.saylor.org/course/bio101 might be helpful. No programming is required for this course although some command line work (though within a web browser) occurs in the 5th module.
Bioinformatic Methods II is regularly updated, and was last updated for January 2024. The past 15 years have been exciting ones in plant biology. Hundreds of plant genomes have been sequenced, RNA-seq has enabled transcriptome-wide expression profiling, and a proliferation of "-seq"-based methods has permitted protein-protein and protein-DNA interactions to be determined cheaply and in a high-throughput manner. These data sets in turn allow us to generate hypotheses at the click of a mouse. For instance, knowing where and when a gene is expressed can help us narrow down the phenotypic search space when we don't see a phenotype in a gene mutant under "normal" growth conditions. Coexpression analyses and association networks can provide high-quality candidate genes involved in a biological process of interest. Using Gene Ontology enrichment analysis and pathway visualization tools can help us make sense of our own 'omics experiments and answer the question "what processes/pathways are being perturbed in our mutant of interest?" Structure: each of the 6 week hands-on modules consists of a ~2 minute intro, a ~20 minute theory mini-lecture, a 1.5 hour hands-on lab, an optional ~20 minute lab discussion if experiencing difficulties with lab, and a ~2 minute summary.
Tools covered [Material updated in June 2024]:
Module 1: GENOMIC DBs / PRECOMPUTED GENE TREES / PROTEIN TOOLS. Araport, TAIR, Gramene, EnsemblPlants Compara, PLAZA; SUBA5 and Cell eFP Browser, 1001 Genomes Browser
Module 2: EXPRESSION TOOLS. eFP Browser / eFP-Seq Browser, Araport, ARDB, TravaDB, NCBI Genome Data Viewer for exploring RNA-seq data for many plant species, MPSS database for small RNAs
Module 3: COEXPRESSION TOOLS. ATTED II, Expression Angler, AraNet, AtCAST2
Module 4: PROMOTER ANALYSIS. Cistome, MEME, ePlant
Module 5: GO ENRICHMENT ANALYSIS AND PATHWAY VIZUALIZATION. AgriGO, AmiGO, Classification SuperViewer, TAIR, g:profiler, AraCyc, MapMan (optional: Plant Reactome)
Module 6: NETWORK EXPLORATION. Arabidopsis Interactions Viewer 2, ePlant, TF2Network, Virtual Plant, GeneMANIA The past 15 years have been exciting ones in plant biology. Hundreds of plant genomes have been sequenced, RNA-seq has enabled transcriptome-wide expression profiling, and a proliferation of "-seq"-based methods has permitted protein-protein and protein-DNA interactions to be determined cheaply and in a high-throughput manner. These data sets in turn allow us to generate hypotheses at the click of a mouse or tap of a finger. In Plant Bioinformatics on Coursera.org, we covered 33 plant-specific online tools from genome browsers to transcriptomic data mining to promoter/network analyses and others, and in this Plant Bioinformatics Capstone we'll use these tools to hypothesize a biological role for a gene of unknown function, summarized in a written lab report.
This course is part of a Plant Bioinformatics Specialization on Coursera, which introduces core bioinformatic competencies and resources, such as NCBI's Genbank, Blast, multiple sequence alignments, phylogenetics in Bioinformatic Methods I, followed by protein-protein interactions, structural bioinformatics and RNA-seq analysis in Bioinformatic Methods II, in addition to the plant-specific concepts and tools introduced in Plant Bioinformatics and the Plant Bioinformatics Capstone.
This course/capstone was developed with funding from the University of Toronto's Faculty of Arts and Science Open Course Initiative Fund (OCIF) and was implemented by Eddi Esteban, Will Heikoop and Nicholas Provart. Asher Pasha programmed a gene ID randomizer.
|
4 course series
|
Beginner level
|
2 months (at 10 hours a week)
|
https://www.coursera.org/specializations/plant-bioinformatic-methods
| null |
915 |
Knowing the Universe: History and Philosophy of Astronomy
|
5,068
|
4.7
| 28 |
Chris Impey
|
University of Arizona
|
[]
|
This is an introductory level course about the history and philosophy of astronomy, the oldest science. We'll look at how humans learned to ask questions about the universe, and even before the invention of modern instruments like the telescope, learned some amazing things about their place in nature. We will start with prehistoric cultures who kept accurate calendars and move through the time of the Greek philosophers who laid down the rudiments of logic and mathematics and the modern scientific method. We'll then examine the revolutions of Copernicus, Galileo, and Newton that redefined our place in the universe. We will then learn about the revolutions in physics in the early 20th century that redefined our ideas of space and time, mass and energy. Finally, we will discuss how modern cosmology has shown us that we live in an ancient universe (14 billion years old), in one galaxy in a universe of hundreds of billions of galaxies. At the end, will ask questions that don't necessarily have answers. What came before the Big Bang? Is there anything outside our universe? What is reality? We'll finish by looking at the role of life in the universe and ask whether the earth is the only place with biology on it. This module welcomes students to the course and explains the structure and assignments of the class. 2 videos3 readings2 assignments What was the Early History of Astronomy? From the Neolithic era to the Classical Greek era, we explore the origins of humanity’s fascination with the night sky and the practical applications of their observations and discoveries. 12 videos6 assignments1 peer review In this module we discuss the contributions made to the field of by different civilizations during the Middle Ages. We also explore, with the coming of the Renaissance, how the field of astronomy evolved due to the contributions of Kepler, Brahe, and Galileo. 14 videos6 assignments1 peer review The scientific revolution had a far-reaching impact on the field of astronomy. From Kepler’s laws of planetary motion to Newton’s theory of universal gravity, the Golden Age of Science brings with it new tools and methods to understand the universe and our place in it. Additionally, we discuss how the study of the universe gives us insight into the history of our home planet. 14 videos7 assignments1 peer review This module explores the creation of different astronomical tools and methods used to observe and gather data from the night sky. We then jump to Einstein, his theory of relativity, and how our modern observations give confirmation to the validity of this theory. 12 videos6 assignments1 peer review What are stars? How are they created? How and why do they die? By closely examining atomic theory, the answers to all these questions and more are discussed in this module. 12 videos5 assignments1 peer review This module answers the “big questions": how was the universe created, how old is the universe, and will the universe come to and end? Galactic and super-galactic structures are examined as well. 13 videos6 assignments1 peer review This module attempts to answer one of humanity’s most pressing questions: are we alone in the universe? Through the discussion of exoplanets and astrobiology, we hope to shed some light on this matter. 7 videos4 assignments1 peer review
|
8 modules
|
Beginner level
|
32 hours to complete (3 weeks at 10 hours a week)
|
https://www.coursera.org/learn/knowing-the-universe
| null |
916 |
CISSP Crash Course
|
Enrollment number not found
|
Rating not found
| null |
Packt - Course Instructors
|
Packt
|
['risk management', 'SDLC', 'CISSP', 'Certified Information Systems Security Professional (CISSP)', 'Risk Management', 'Availability', 'availability', 'vulnerability']
|
This comprehensive course covers the full breadth of the CISSP certification, spanning all eight domains. You will begin with Security and Risk Management, exploring essential concepts such as governance, legal regulations, and business continuity. Through detailed lessons on compliance and investigation requirements, you’ll build a solid foundation in risk management and threat modeling. Each video is crafted to clarify intricate ideas, preparing you for real-world security challenges. Moving forward, the course delves into Asset Security and Architecture & Engineering. You will learn about data classification, secure provisioning, and security models, alongside cryptographic solutions and the design of secure systems. The focus on practical applications, such as network security and secure communication, equips you to handle complex security architectures and operational scenarios with confidence.
The latter part of the course emphasizes Identity and Access Management, Security Assessment, and Security Operations. You will master identity lifecycles, authentication systems, and access controls, followed by in-depth analysis of security testing, operations, and software development security. By the end of this course, you will possess the expertise to implement, manage, and assess security systems in any enterprise environment, making you an ideal candidate for CISSP certification.
This course is ideal for IT security professionals, network engineers, and anyone preparing for the CISSP exam. A basic understanding of security concepts is recommended to fully benefit from this course. In this module, we will explore the critical aspects of security and risk management, beginning with foundational concepts and progressing through governance, compliance, and legal frameworks. You will also learn key topics such as risk management, business continuity, personnel security, and threat modeling, culminating in strategies for managing supply chain risks and delivering effective security training. 11 videos In this module, we will focus on the management and security of information assets, covering topics such as data classification, asset handling, and secure provisioning. You'll gain an understanding of the roles involved in managing data, how to handle asset retention at different stages of its lifecycle, and how to apply security controls and compliance requirements to protect organizational resources. 6 videos In this module, we will delve into the architectural and engineering processes crucial to building secure systems. Topics will cover security models, cryptographic solutions, and security controls development. You’ll also learn about the security of different system types, including databases and microservices, while understanding cryptanalytic attacks and the integration of security principles into facility design. 10 videos1 assignment In this module, we will explore the foundational elements of communication and network security. You will learn how to design secure networks by understanding the OSI and TCP/IP models, implement robust network hardware and components, and ensure secure communication protocols to protect data during transmission. 3 videos In this module, we will cover the principles of identity and access management, focusing on controlling access to both physical and logical assets. You will learn about managed identification, federated identities, and authorization processes, along with key authentication systems like SSO, OpenID, and OAuth, ensuring secure and efficient access control throughout the identity lifecycle. 6 videos In this module, we will examine the processes involved in security assessment and testing. You will learn how to design and validate assessments and audits, test security controls, and gather critical security data. Additionally, we will focus on analyzing test outputs and creating detailed reports to enhance organizational security measures. 4 videos1 assignment In this module, we will explore the key elements of security operations, including investigation procedures, logging and monitoring, and configuration management. You’ll also learn about resource protection, the operation of detective and preventative controls, vulnerability management, and response strategies for disasters, along with essential practices for physical security and safety. 9 videos In this module, we will focus on the integration of security within the software development process, emphasizing the importance of secure methodologies and maturity models in the SDLC. You’ll learn about security controls in each development phase, how to assess software security through audits, and how to implement secure coding guidelines to prevent common software vulnerabilities. 4 videos2 assignments
|
8 modules
|
Advanced level
|
8 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/packt-cissp-crash-course-mvewu
| null |
917 |
Using Public Policy for Social Change
|
9,536
|
4.9
| 84 |
Paula Lantz
|
University of Michigan
|
['Policy Analysis', 'Problem Solving', 'Policy Design', 'Policy Advocacy', 'Social Issues']
|
Using Public Policy for Social Change provides a comprehensive introduction to public policy and its role in addressing societal challenges, with a focus on social inequalities. You’ll explore various areas of policy work, including social welfare, public health, the environment, education, and criminal justice. Learn the fundamentals of public policy design and analysis, and how policymaking functions across all levels of government in democracies worldwide. The course offers the opportunity to delve into social issues you care about, learn from real-life policymakers and advocates, and strengthen your analytical, critical thinking, and advocacy skills to create positive social change. Using Public Policy for Social Change leads you through each step of the policymaking process and encourages you to see how your talents and passions can play a role in making the world a more equitable place. Welcome to the Using Public Policy for Social Change course and the first-week module! This module provides an overview of the course and introduces learners to public policy as a field of professional practice. This includes an introduction to key concepts and terms and to a framework for understanding the policy-making process in democracies. Let's get started! 16 videos6 readings3 assignments2 discussion prompts Welcome to Week 2! This module focuses on the first two steps in the policy-making cycle: “issue framing and “agenda setting.” This includes attention to how social problems can be researched, framed, and advocated for using an equity lens. This week will also include instruction in the basic elements of designing and implementing an advocacy strategy regarding a policy issue. Let's get started! 13 videos4 readings2 assignments1 app item2 discussion prompts Welcome to Week 3! You passed the midpoint of this course. Great job! This module focuses on steps three and four in the policy-making process of policy design, which includes policy design and policy decision-making. We cover the basics of the policy design and the important role of prospective policy analysis in the process. The module will also present a framework for analyzing and justifying a specific policy idea/design that includes consideration of its impact, economic efficiency, ethical tensions, and equity/fairness implications. Let's get started! 11 videos3 readings5 assignments1 app item1 discussion prompt Welcome to Week 4, the last week of this course! This module covers steps five and six in the policy-making cycle: policy implementation and policy evaluation. The focus of this module is on the major techniques used to assess whether public programs and policies are achieving their intended objectives and goals. The module includes a discussion of different types of program evaluation for assessing implementation and impact/outcome goals and the research approaches commonly used for public sector evaluation, including many examples. This module also provides some guidance regarding how to find resources related to policy evaluation research and other aspect of public policy. The module concludes with an overview of the course, along with some guidance for how to find your own niche in the world of using public policy for social change. Let's get started! 13 videos3 readings3 assignments2 discussion prompts
|
4 modules
|
Beginner level
|
14 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/using-public-policy-for-social-change
| null |
918 |
Sensory Science: Conducting Tests
|
Enrollment number not found
|
4.8
| 12 |
Rebecca Bleibaum
|
University of California, Davis
|
[]
|
This course will introduce the sensory evaluation laboratory and will teach you best practices for testing and documentation. We'll explore how various factors, especially the testing environment, can influence sensory experiments. Our main focus will be on two specific sensory tests: duo-trio discrimination and 3-product consumer testing. Through case studies, we’ll examine how these tests can address product challenges. For both test types, we’ll dive into how to develop an appropriate hypothesis, select products, execute a sensory test, decode collected data, and interpret the test results. Additionally, you’ll learn how to identify and select core and opportunity target groups of consumers. Each module in this course builds towards your final project where you will design a sensory test to conduct your own research experiment. Welcome to the last course in the Foundations of Sensory Science series! In this course, we will introduce the sensory evaluation laboratory and teach you how to conduct two types of research experiments: a discrimination test and a 3-product consumer test. In this module, you will learn about errors in testing and ways to minimize those errors to ensure valid and reliable sensory data. You will review principles for recruiting qualified assessors for each test type and discuss ways to instruct assessors and the importance of documenting test instructions. This course will describe best practices testing procedures and ways that a sensory experiment can be influenced, especially the test environment. Let’s get started! 9 videos2 readings1 assignment2 discussion prompts In this module, we will begin by discussing discrimination testing methods and what problems they might solve for product issues. You will review various case studies that illustrate common business problems where discrimination testing was beneficial. You will review approaches to establishing a research objective using a balanced reference duo-trio test and the importance of product selection will be discussed. We will identify best practices qualification criteria for sensory analytical tests – discrimination testing and descriptive analysis. This module will teach you the principles of conducting your own research experiment based on discrimination testing principles. We will discuss how to develop an appropriate hypothesis, select products, prepare and conduct testing, decode the data, and interpret the results. In this module you’ll also start developing a sensory test using the tools you’ll gain throughout this course. Let’s begin! 16 videos1 reading1 assignment1 discussion prompt In this module, we will continue our discussion by reviewing a different style of sensory testing: consumer product testing. You’ll review consumer product testing methods and how they apply to sensory science. We’ve previously formulated a hypothesis and research objectives. We will now discuss product selection for conducting a consumer test, and review how to identify and select a core and opportunity target group of consumers. We will review the importance of balanced serving orders and discuss how to prepare and conduct a 3-product consumer test. This module will teach you the principles of conducting your own research experiment based on consumer product testing principles. We will discuss how to develop an appropriate hypothesis, select products, prepare and conduct testing, decode the data, and interpret the results. For your final project, you will select and conduct either a duo-trio discrimination test or a 3-product consumer test. You will continue to design the various research components that will be used to build your final project. Both research experiments are designed as paper/pencil activities to aid in the learning process. Let’s get started! 16 videos1 reading1 assignment1 discussion prompt In this final module, everything you’ve worked on in the previous modules will come together to complete your project. You will apply the design of your sensory test to conduct a research experiment. You’ll use the testing method, and its principles, you selected in module 3 (either the duo-trio discrimination test or the 3-product consumer test) to conduct your test. You’ll develop the appropriate set of testing materials for the test you selected, as outlined in the program. You will also report on your own research experiment by preparing and reporting your data and key findings. For the final project, you’ll report your findings in the form of a discussion forum and through a graded self-assessment by demonstrating your comprehension of sensory science principles. 2 videos1 reading1 assignment2 discussion prompts
|
4 modules
|
Intermediate level
|
12 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/sensory-science-conducting-tests
| null |
919 |
21st Century Energy Transition: how do we make it work?
|
6,279
|
4.9
| 84 |
Brad Hayes
|
University of Alberta
|
[]
|
Affordable, abundant and reliable energy is fundamental to human well-being and prosperity. For the past 150 years, more and more people have gained access to energy, primarily in the form of fossil fuels – coal, petroleum and natural gas. But now, even while half of humanity cannot access adequate energy supplies, we are beginning a profound transition to more diverse energy sources. Climate change, environmental sustainability, and energy poverty are all important – and sometimes conflicting – drivers as we strive to supply more energy to more people with fewer negative impacts on Earth’s environments. In this course from the University of Alberta and Canadian Society for Evolving Energy, you will join us to learn about the many energy sources available, and where technology is providing exciting new solutions to energy and environmental challenges. Find out what roles energy storage must play to support the transition, and discuss how we can optimize transition processes. Examine competing viewpoints (“realities”) to enable energy transition, focusing on the practical challenges in bringing about change on a global basis. Finally, you will bring all these issues together to examine how the energy transition process is progressing and what we must do to create pathways to achieve our goals. Welcome to 21st Century Energy Transitions- how do we make it work? In this first module, we will introduce one of the great global challenges of our time: how do we deliver dependable global energy in a way that mitigates the effects of human-induced climate change, encourages sustainability, and meets the sometimes competing economic needs of many different countries? To begin answering this question, we will also dive into the past to discover how energy has transitioned throughout human history, and see how this might help us with energy transitions today. 2 videos1 reading1 assignment1 discussion prompt To understand the challenges and opportunities of global energy transition, we need to be aware of the different energy sources that are used today, and those that could be more dominant in the future. From fossil fuels and established renewables like solar and wind, to more recent advances in energy sources like biomass and geothermal, in this module we'll introduce each major player in the world of energy, discuss their benefits, challenges, and see some new technology that might provide solutions to future energy issues. 13 videos1 reading3 assignments2 discussion prompts Now that we've covered the major energy sources, it's time to switch focus to another important part of the energy transition- energy storage. In this module we'll look at energy storage requirements and priorities, particularly in relation to electricity. We'll also examine hydrogen as a potential source of low GHG energy, discuss its positive and negative attributes, and explore some new technologies making hydrogen more available and competitive. 3 videos1 reading1 assignment Congratulations! You've made it to the second half of the course! Now that we're comfortable with energy sources and storage technologies, it's time to ask some of the tough questions for the energy transition over the next century. How do we balance rising energy demands and increasing populations with reducing GHG emissions? How do we improve energy efficiency both as populations and individuals? What are some ways that we can keep GHG emissions as low as possible in future scenarios where fossils fuels will still be required? How do we balance rapid change with continuous energy delivery? How do we reconcile the competing energy policies of different countries? As you'll see in this module, there are very few clear answers, but the 21st century energy transition starts with asking the right questions. 4 videos1 reading1 assignment1 discussion prompt In this module, we will explore the two most common viewpoints on the rate of energy transition: Reality 1 and Reality 2. In Reality 1, energy transition will be a measured, gradual process focused on reducing GHG emissions, driven primarily by market forces with diverse energy portfolios. In Reality 2, transition is a more urgent process because the world is facing a climate crisis. Focus is on reducing GHG emissions, with major energy reforms, including the elimination of fossil fuels now or in the near future. We will examine both points of view, discussing their requirements, challenges and implications. 3 videos1 reading1 assignment1 discussion prompt Well done on reaching the final module of the course! In this module, we will switch the focus of our discussion from the energy sectors, to the governments and policy makers enacting legislation and guidelines to steer the energy transition. We'll have a look at some current policies, and ask whether stepping stones have been put in place to achieve realistic targets. We will also discuss the many things that we can do better in terms of communication, flexible and logical thinking, and recognizing viewpoints of various stakeholders. Finally, we'll reflect on what we've learned throughout the course and hopefully, find ourselves better equipped to answer our titular question: how do we make the 21st century energy transition work? 3 videos1 reading1 assignment1 discussion prompt
|
6 modules
|
Beginner level
|
16 hours to complete (3 weeks at 5 hours a week)
|
https://www.coursera.org/learn/21st-century-energy-transition
| null |
920 |
Google Cloud Digital Leader Training Professional Certificate
|
51,333
|
4.8
| 2,603 |
Google Cloud Training
|
Google Cloud
|
[]
|
The Cloud Digital Leader training consists of a course series designed to give you foundational knowledge about cloud technology and data. This training also offers an overview of Google Cloud products and services that enable organizations’ digital transformation. This training will empower you and your team(s) to contribute to cloud-related business initiatives across your organization. This training builds knowledge in these areas: General cloud knowledge General Google Cloud knowledge Google Cloud products and services Digital transformation, data, and AI/ML Modernizing company IT infrastructure and applications Applied Learning Project Students will have an opportunity to validate their knowledge gained throughout each of the courses with practice and graded assessments at the end of each module and for each course. Practice and graded assessments are used to validate and demonstrate learning outcomes. Explain why and how the cloud revolutionizes businesses. Explain general cloud concepts. Discuss the benefits and tradeoffs of using Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Examine the value of data and how it affects customer experiences. Explore the different Google Cloud data management solutions that are available. Learn about the ways Google Cloud products have made data more useful and accessible to a workforce. Explore key artificial intelligence and machine learning concepts. Describe ways machine learning can create value for businesses. Examine Google Cloud artificial intelligence and machine learning products and services. Understand the role that cloud modernization and migration plays in an organization's digital transformation. Examine available options to run compute workloads in the cloud. Explore the advantages of using containers, serverless computing, and APIs in application modernization. Learn about the business reasons to choose hybrid or multi-cloud strategies, and how GKE Enterprise can help support these strategies. Identify fundamental security concepts. Explore the business value of Google’s defense-in-depth multilayered approach to infrastructure security. Learn how Google Cloud works to earn and maintain customer trust in the cloud. Learn how Google Cloud can help organizations manage cloud finances and costs. Explore the basic concepts of modern cloud operations, reliability, and resilience. Learn how Google Cloud helps organizations reach their sustainability goals and reduce their environmental impact.
|
6 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/professional-certificates/google-cloud-digital-leader-training
| null |
921 |
Getting Started with Tableau
|
3,171
|
4.6
| 20 |
Skill-Up EdTech Team
|
SkillUp EdTech
|
['Data Analysis', 'Tableau (Business Intelligence Software)', 'Dashboard', 'Tableau Software', 'Data Visualization']
|
This short course is designed for anyone seeking to unlock the full potential of Tableau Public, a leading data visualization tool. Starting from the fundamentals, you will progress through each module, gaining hands-on experience in importing, exploring, and visualizing data. From creating basic visualizations to designing interactive dashboards and compelling stories, this course covers it all. You will explore real-time data updates, ensuring adaptability, and master the art of storytelling in data visualization, crafting effective Tableau stories with customization and adherence to best practices.
Practical exercises based on real-world scenarios throughout the course ensure the knowledge you gain isn’t just theoretical but aligns with the skills employers are looking for.
Start building the foundation to harness the power of Tableau for effective data visualization and analysis today. This module introduces you to the business intelligence tool Tableau and familiarizes you with its fundamental and primary capabilities regarding data manipulation. You will learn to download, import, and view data in Tableau. In learning about working with data in Tableau, you will also learn about some data vocabulary and concept basics. You explore the Tableau interface, including filtering, worksheet formatting, and calculating. You will view some sample visualizations to discover Tableau’s visualization capabilities and create some visualizations yourself. 8 videos2 readings3 assignments4 plugins In this module, you learn how to create engaging visualizations to add to your Tableau workbook by using advanced visualization elements, filters, and highlighting. You also learn about dashboards and how to use them to create effective stories with your data. You explore principles of interactive dashboard design and best practices when creating them. Specifically, you learn how to organize visual elements, design interactive aspects, and use real-time data. Then, you use what you’ve learned in Tableau to tell an effective story to your audience about your data. 10 videos1 reading4 assignments8 plugins In this module, you will read a scenario overview for your final project, and then use that scenario and the information provided to build a final project which will be assessed by your peers. You will also complete a final quiz which is graded to help assess your understanding of the topics of this course. 3 readings1 assignment1 peer review2 plugins
|
3 modules
|
Beginner level
|
12 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/getting-started-with-tableau
| null |
922 |
Getting Started With Music Theory
|
111,883
|
4.5
| 745 |
Bruce Taggart
|
Michigan State University
|
[]
|
This course is a brief introduction to the elements of music theory for those with little or no music theory experience. We will explore pitch, rhythm, meter, notation, scales, keys, key signatures, meter signatures, triads, seventh chords, and basic harmony. If you listen to music or play music by ear, and you want to know more about how music is organized and notated, this course is for you. By the end of the course, you should know all major and minor keys, how to read and write in treble and bass clef using standard meters and rhythmic values, and how to notate and harmonize a simple melody. This course can serve as a stand-alone basic music theory course, or it can be a springboard to more advanced theory and composition courses.
Your instructor is Bruce Taggart, Associate Professor of Music Theory at Michigan State University, in the College of Music, where he has taught undergraduate and graduate music theory since 1996. Learning Outcomes: By the end of this module, you should be able to: (1) discuss the elements of music, (2) explain the difference between tonal and atonal music, (3) sing the tonic in tonal music, (4) identify the fundamental and partials of a note, (5) explain the difference between chord and harmony, (6) explain the five-line staff, (7) read and write notes using treble and bass clefs, and (8) identify rhythmic values in notation. You should be able to (9) distinguish between pitch and pitch class, (10) describe octaves and how to label pitches based on octave placement, (11) identify and write accidentals and find them on the piano keyboard, (12) and define equal temperament (the artificial scale used on the modern piano) and tell how it differs from other tuning systems. 9 videos1 reading4 assignments2 discussion prompts Learning Outcomes: By the end of this module, you should be able to (1) describe the diatonic set and understand how it is used to create major and minor scales, (2) sing major and minor using solfeggio (solfege) syllables, (3) explain the difference between natural, harmonic, and melodic minor, (4) spell major and minor scales starting on any note using accidentals in treble and bass clef, and (5) spell parallel and relative major and minor scales. You should also be able to (6) identify and spell by size and quality diatonic intervals (within a key) and chromatic intervals (outside a key). 12 videos3 readings4 assignments2 discussion prompts Learning Outcomes: By the end of this module, you should be able to (1) read and write all possible rhythmic values, including dotted notes and ties, (2) understand how many notes fit within a measure in various meters, (3) determine meter signatures based on note grouping, and note grouping based on meter signatures, (4) define the types of musical accent and how they create a sense of meter, (5) distinguish between duple and triple meters in notation and by sound, and (6) describe and identify metrical syncopation. You should be able to (7) write melodies on the treble, bass, and grand staves using correct meter signatures, note values, rhythmic grouping, stem direction and beaming, and key signatures and accidentals, 6 videos2 readings2 assignments1 discussion prompt Learning Outcomes: By the end of this module, you should be able to (1) identify and spell major, minor, diminished, and augmented triads in root position and inversions, and (2) identify and spell major, minor, dominant, half-diminished, and fully diminished seventh chords in root position and inversions. You should also be able to (3) use Roman numeral labels to identify diatonic triads within a key, (4) write triads within a key when given Roman numerals, and (5) spell chords when given pop/jazz chord symbols. 8 videos3 readings3 assignments2 discussion prompts
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/music-theory
|
92%
|
923 |
Introduction to Accounting Data Analytics and Visualization
|
28,859
|
4.8
| 435 |
Ronald Guymon
|
University of Illinois Urbana-Champaign
|
['Predictive Analytics', 'Data Analysis', 'Coding', 'Data Visualization', 'Data Architecture']
|
Accounting has always been about analytical thinking. From the earliest days of the profession, Luca Pacioli emphasized the importance of math and order for analyzing business transactions. The skillset that accountants have needed to perform math and to keep order has evolved from pencil and paper, to typewriters and calculators, then to spreadsheets and accounting software. A new skillset that is becoming more important for nearly every aspect of business is that of big data analytics: analyzing large amounts of data to find actionable insights. This course is designed to help accounting students develop an analytical mindset and prepare them to use data analytic programming languages like Python and R. We’ve divided the course into three main sections. In the first section, we bridge accountancy to analytics. We identify how tasks in the five major subdomains of accounting (i.e., financial, managerial, audit, tax, and systems) have historically required an analytical mindset, and we then explore how those tasks can be completed more effectively and efficiently by using big data analytics. We then present a FACT framework for guiding big data analytics: Frame a question, Assemble data, Calculate the data, and Tell others about the results.
In the second section of the course, we emphasize the importance of assembling data. Using financial statement data, we explain desirable characteristics of both data and datasets that will lead to effective calculations and visualizations.
In the third, and largest section of the course, we demonstrate and explore how Excel and Tableau can be used to analyze big data. We describe visual perception principles and then apply those principles to create effective visualizations. We then examine fundamental data analytic tools, such as regression, linear programming (using Excel Solver), and clustering in the context of point of sale data and loan data. We conclude by demonstrating the power of data analytic programming languages to assemble, visualize, and analyze data. We introduce Visual Basic for Applications as an example of a programming language, and the Visual Basic Editor as an example of an integrated development environment (IDE). In this module, you will become familiar with the course, your instructor and your classmates, and our learning environment. This orientation module will also help you obtain the technical skills required to navigate and be successful in this course. 2 videos6 readings1 discussion prompt1 plugin In this module, you will learn how the accounting profession has evolved. You will recognize how data analytics has influenced the accounting profession and how accountants have the ability to impact how data analytics is used in the profession, as well as in an organization. Finally, you will learn how data analytics is influencing the different subdomains within accounting. 12 videos2 readings3 quizzes1 discussion prompt In this module, you will learn to recognize the importance of making room for empirical enquiry in decision making. You will explore characteristics of an analytical mindset in business and accounting contexts, and link those to your core courses. You will then evaluate a framework for making data-driven decisions using big data. 12 videos2 readings4 quizzes This module looks at specific characteristics of data that make it useful for decision making. 12 videos2 readings3 quizzes In this module, you will learn fundamental principles that underlie data visualizations. Using those principles, you will identify use cases for different charts and learn how to build those charts in Excel. You will then use your knowledge of different charts to identify alternative charts that are better suited for directing attention. 17 videos2 readings4 quizzes1 peer review In this module, you’ll learn how to use Tableau to do with data what spies do when observing their surroundings: get an overview of the data, narrow in on certain aspects of the data that seem abnormal, and then analyze the data. Tableau is a great tool for facilitating the overview, zoom, then filter details-on-demand approach. Tableau is a lot like a more powerful version of Excel's pivot table and pivot chart functionality. 13 videos2 readings3 quizzes In this module, you'll be guided through a mini-case study that will illustrate the first three parts of the FACT model, with a focus on the C, or calculations part of the FACT model. First, you will perform a correlation analysis to identify two-way relationships, and analyze correlations using a correlation matrix and scatter plots. You will then build on your knowledge of correlations and learn how to perform regression analysis in Excel. Finally, you will learn how to interpret and evaluate the diagnostic metrics and plots of a regression analysis. 13 videos2 readings4 quizzes1 peer review In this module, you’ll learn how the regression algorithm can be applied to fit a wide variety of relationships among data. Specifically, you’ll learn how to set up the data and run a regression to estimate the parameters of nonlinear relationships, categorical independent variables. You’ll also investigate if the effect of an independent variable depends on the level of another independent variable by including interaction terms in the multiple regression model. Another aspect of this module is learning how to evaluate models, regression or otherwise, to find the most favorable levels of the independent variables. For models that explain revenue, the most favorable levels of the independent variables will maximize revenue. In contrast, if you have a model that describes costs, like a budget, then the most favorable levels of the independent variables will minimize costs. Optimizing models can be difficult because there are so many inputs and constraints that need to be managed. In this module, you’ll learn how to use the Solver Add-In to find the optimal level of inputs. For some models, the dependent variable is a binary variable that has only two values, such as true/false, win/lose, or invest/not invest. In these situations, a special type of regression, called logistic regression, is used to predict how each observation should be classified. You’ll learn about the logit transformation that’s used to convert a binary outcome to a linear relationship with the independent variables. Excel doesn’t have a built-in logistic regression tool, so you’ll learn how to manually design a logistic regression model, and then optimize the parameters using the Solver Add-In tool. 12 videos2 readings3 quizzes The lessons in this module are organized around several useful tasks, including stacking multiple dataframes together into one dataframe, creating multiple histograms to accompany the descriptive statistics, and learning how to perform k-means clustering. After going through this module, you’ll not only gain a foundation to help you understand coding, but you’ll also learn more about analyzing financial data. Along the way, I hope that you’ll also pick up on a few other useful Excel functions. 14 videos4 readings4 quizzes1 plugin
|
9 modules
|
Beginner level
| null |
https://www.coursera.org/learn/intro-accounting-data-analytics-visual
|
93%
|
924 |
Genomic Data Science and Clustering (Bioinformatics V)
|
16,022
|
4.2
| 90 |
Pavel Pevzner
|
University of California San Diego
|
[]
|
How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters. In the first half of the course, we will introduce algorithms for clustering a group of objects into a collection of clusters based on their similarity, a classic problem in data science, and see how these algorithms can be applied to gene expression data.
In the second half of the course, we will introduce another classic tool in data science called principal components analysis that can be used to preprocess multidimensional data before clustering in an effort to greatly reduce the number dimensions without losing much of the "signal" in the data.
Finally, you will learn how to apply popular bioinformatics software tools to solve a real problem in clustering. <p>Welcome to class!</p><p>At the beginning of the class, we will see how algorithms for <strong>clustering </strong>a set of data points will help us determine how yeast became such good wine-makers. At the bottom of this email is the Bioinformatics Cartoon for this chapter, courtesy of <a href="http://bearandfox.com" target="_blank" title="Link: http://bearandfox.com">Randall Christopher</a> and serving as a chapter header in the Specialization's bestselling <a href="http://bioinformaticsalgorithms.com" target="_blank">print companion</a>. How did the monkey lose a wine-drinking contest to a tiny mammal? Why have Pavel and Phillip become cavemen? And will flipping a coin help them escape their eternal boredom until they can return to the present? Start learning to find out!</p><p><img width="550" alt="" src="http://bioinformaticsalgorithms.com/images/cover/clustering_cropped.jpg" title="Image: http://bioinformaticsalgorithms.com/images/cover/clustering_cropped.jpg"></p> 5 videos2 readings1 assignment2 app items <p>Welcome to week 2 of class!</p>
<p>This week, we will see how we can move from a "hard" assignment of points to clusters toward a "soft" assignment that allows the boundaries of the clusters to blend. We will also see how to adapt the Lloyd algorithm that we encountered in the first week in order to produce an algorithm for soft clustering. We will also see another clustering algorithm called "hierarchical clustering" that groups objects into larger and larger clusters.</p> 5 videos1 reading1 assignment2 app items 2 readings1 assignment
|
3 modules
|
Intermediate level
|
9 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/genomic-data
| null |
925 |
Learn to Teach Java Specialization
|
2,992
|
4.7
| 45 |
Beth Simon
|
University of California San Diego
|
['Computer Programming', 'Teaching', 'Java', 'Pedagogy', 'teacher']
|
Learn to teach introductory Java -- with a focus on the new Advanced Placement Computer Science A curriculum. Preview the CS Awesome curriculum with overview videos to help you prepare for class efficiently. Learn teaching tips and access supporting materials from an expert in CS education with 15+ years experience including advice on teaching debugging, code tracing (for answering multiple choice questions) and problem solving patterns. Complete activities specifically designed for teachers and create materials you can use in your classroom. Applied Learning Project In this specialization you will engage in projects to develop resources for your classroom to supplement the CS Awesome online interactive textbook as well as evaluate other curricula which might be useful for you. Additionally, you will develop resources, assessments, and instructional plans and materials you can use in YOUR classrooms. Get started with the basics of Java, and prepare to teach others using the free, online interactive CS Awesome textbook. In this course for teachers we'll guide you both in learning Java concepts and skills but also in how to effectively teach those to your students. This course will support you in teaching the Advanced Placement Computer Science A course or a similar introductory university-level programming course. We'll begin with simple instruction sequences, primitive types, and using objects, as covered in the APCS A Units 1 and 2. Each topic will begin by relating Java to block-based programming languages and then provide video overviews of CS Awesome content along with additional materials to supplement learning for your students.
You'll engage with additional materials to support your teaching including "deep dive" classroom discussion questions and assessment overviews and options for your students. Learn to program with Boolean Expressions, If Statement, and For and While Loops in Java, and prepare to teach others using the free, online interactive CS Awesome textbook. In this course for teachers we'll guide you both in learning Java concepts and skills but also in how to effectively teach those to your students. This course will support you in teaching the Advanced Placement Computer Science A course or a similar introductory university-level programming course. We'll cover the critical Java concepts of selection (if statements) and iteration (loops), as covered in the APCS A Units 3 and 4. Each topic will begin by relating Java to block-based programming languages and then provide video overviews of CS Awesome content along with additional materials to supplement learning for your students.
You'll engage with additional materials to support your teaching including "deep dive" classroom discussion questions, assessment overviews, code tracing and problem solving skills for your students, including preparation for free response coding questions. Learn to program using Class design and 1-D Arrays in Java, and prepare to teach others using the free, online interactive CS Awesome textbook. In this course for teachers we'll guide you both in learning Java concepts and skills but also in how to effectively teach those to your students. This course will support you in teaching the Advanced Placement Computer Science A course or a similar introductory university-level programming course. We'll cover the critical Java concepts of class design and 1-dimensional arrays, as covered in the APCS A Units 5 and 6. Each topic will begin by relating Java to block-based programming languages and then provide video overviews of CS Awesome content along with additional materials to supplement learning for your students.
You'll engage with additional materials to support your teaching including "deep dive" classroom discussion questions, assessment overviews, code tracing and problem solving skills for your students, including preparation for free response coding questions. Learn to program with ArrayLists and 2-D Arrays in Java, and prepare to teach others using the free, online interactive CS Awesome textbook. In this course for teachers we'll guide you both in learning Java concepts and skills but also in how to effectively teach those to your students. This course will support you in teaching the Advanced Placement Computer Science A course or a similar introductory university-level programming course. We'll cover the Java concepts of ArrayLists and 2-dimensional arrays, as covered in the APCS A Units 7 and 8. Each topic will begin by relating Java to block-based programming languages and then provide video overviews of CS Awesome content along with additional materials to supplement learning for your students.
You'll engage with additional materials to support your teaching including "deep dive" classroom discussion questions, assessment overviews, code tracing and problem solving skills for your students, including preparation for free response coding questions. Learn to program with Inheritance and Recursion in Java, and prepare to teach others using the free, online interactive CS Awesome textbook. In this course for teachers we'll guide you both in learning Java concepts and skills but also in how to effectively teach those to your students. This course will support you in teaching the Advanced Placement Computer Science A course or a similar introductory university-level programming course. We'll cover the Java concepts of inheritance and recursion, as covered in the APCS A Units 9 and 10. Each topic will begin by relating Java to block-based programming languages and then provide video overviews of CS Awesome content along with additional materials to supplement learning for your students.
You'll engage with additional materials to support your teaching including "deep dive" classroom discussion questions, assessment overviews, code tracing and problem solving skills for your students, including preparation for free response coding questions.
|
5 course series
|
Beginner level
|
2 months (at 10 hours a week)
|
https://www.coursera.org/specializations/teach-java
| null |
926 |
Good with Words: Speaking and Presenting Specialization
|
19,010
|
4.6
| 196 |
Patrick Barry
|
University of Michigan
|
['Confidence', 'Communication', 'Creativity', 'Tact', 'Persuasion']
|
Suppose you were good with words. Suppose when you decided to speak, the message you delivered—and the way you delivered it—successfully connected with your intended audience. What would that mean for your career prospects? What would that mean for your comfort level in social situations? And perhaps most importantly, what would that mean for your satisfaction with the personal relationships you value the most?
This specialization is designed to help you find out. Based on an award-winning course and workshop series at the University of Michigan that has been taken by students training to enter a wide range of fields—law, business, medicine, social work, public policy, design, engineering, and many more—it removes the guesswork from figuring out how to communicate clearly and compellingly. All of us have ideas that are worth sharing. Why not learn to convey yours in a way that people will appreciate, enjoy, and remember? Applied Learning Project This specialization offers you opportunities to practice everything from giving a speech, to pitching an idea, to delivering a meaningful apology. The communication skills you learn can help you solve conflicts, advance a cause, and generally feel more confident about your ability to connect with a wide range of audiences. How to hold the attention of a wide range of audiences How to project a powerful combination of confidence, competence, and charisma How to arrange your content in clear, memorable packages How to use a well-tested suite of rhetorical rhythms to enhance your delivery and linguistic sophistication How to inspire people with a sense of "informed hope" How to treat storytelling as an "entrepreneurial superpower" How to expand your range of dynamic gestures and facial expressions How to increase the creativity you bring to your next negotiation How to incorporate a "little bit of mischief" to your presentations in a way that delights and informs your audience How to use "mirroring" and follow-up questions to establish trust and build rapport How to connect with people via the "language of common life" How to reimagine the experience of starting a conversation with a stranger How to cultivate a "generosity of spirit" when speaking with someone one-on-one How to fire someone respectfully How to reframe your next presentation or performance as a "contribution" How to apologize in a sincere, meaningful way
|
4 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/good-with-words-speaking-and-presenting
| null |
927 |
Introduction to Privacy - Part 3
|
Enrollment number not found
|
Rating not found
| null |
Ralph O'Brien
|
Infosec
|
[]
|
Part 3 of the Privacy Fundamentals explores information security and data protection and how to manage a security breach. We will also take a look at continual improvement which includes understanding performance, exploring metrics, different audit methodologies and more. 3 videos 4 videos 3 videos1 assignment
|
3 modules
| null |
2 hours to complete
|
https://www.coursera.org/learn/introduction-to-privacy---part-3
| null |
928 |
ICT in Primary Education: Transforming children's learning across the curriculum
|
18,953
|
4.6
| 175 |
Professor Diana Laurillard
|
University of London
|
[]
|
Why and how are teachers integrating ICT (Information and Communication Technology) into primary education? In this course we analyse examples from schools in different parts of the world, and bring professional teachers, headteachers and policymakers together to share their best ideas and inspiring stories. The materials in the course are based on studies carried out for the UNESCO Institute of IT in Education, Moscow.
Learning Outcomes:
to be aware of the range of reasons for using ICT
to critique the strategies for developing ICT over time
to analyse the strengths and weakness of different decision-making mechanisms
to become familiar with a wider range of useful tools and resources for integrating ICT This week will enable you to be aware of the range of reasons for using ICT and to critique the strategies for developing ICT over time. You will also analyse the strengths and weakness of different decision-making mechanismsand become familiar with a wider range of useful tools and resources for integrating ICT 7 videos7 readings7 discussion prompts This week will enable you to identify different dimensions of change at the school level due to the integration of ICT and to be aware of new opportunities for global participation facilitated by technology. You will also begin to understand the features involved in effective professional development and be aware of how children perceive the use of technology in a school context 7 videos6 readings7 discussion prompts This week will introduce the primary school teaching community and enable you to contribute to the integration of a range of effective ICT-based practices and pedagogies. In addition we aim to increase understanding of the differences in teaching and learning styles, and how different learning activities can contribute to the depth of learning. 10 videos2 readings1 peer review3 discussion prompts This week we aim to encourage you to know different categories of ICT tools, their affordances and different criteria to be applied when selecting them. As well as be able to analyze the needs for digital content and various strategies how to get it, share, or develop and to be aware of the potential of ICT to support computational thinking, to reflect on the needs, priorities, and future plans for further developing and extending the digital environment. 5 videos2 readings2 peer reviews4 discussion prompts This week we hope to enable you to identify the different dimensions of implementation issues, and apply them to your own context and to become aware of problems that can be encountered in using ICT. We also wish you to share and build some solutions to these concerns and problems and consider these solutions to be of different kinds: learning design, infrastructure, negotiation with parents, communities of practice, policies, staff development, pedagogical innovations, differentiation, affordable access, and teaching support. 10 videos2 readings1 peer review4 discussion prompts This week we aim to explain the pivotal role of the teacher in the ICT-enhanced learning environments and to identify the competencies of the teacher to take up this role effectively in the ICT-enhanced learning environments. As well as explain the conditions for supporting the teachers to take up this role effectively in the ICT-enhanced learning environments 1 video2 readings1 peer review
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/ict-primary-education
|
98%
|
929 |
Comic Books, Geek Culture, and the Fandom Imaginary
|
Enrollment number not found
|
Rating not found
| null |
Christopher Haynes
|
University of Colorado Boulder
|
['Self-Reflection', 'Critical Thinking', 'Communication', 'Culture', 'analysis']
|
"Comic Books, Geek Culture, and the Fandom Imaginary" explores some of the conventional framings of “fandom” (from comic book obsessives to cosplayers) and the cultural histories that sustain it. It also explores the dark side of these dynamics, looking at what can happen when fandom turns toxic in pop culture spaces. You will continue to apply frameworks of self-reflection and close reading/analysis to the study of contemporary popular culture, and explore how those frameworks provide tools for understanding the self as much as our cultural surroundings. The course asks the fundamental question: how can what we love - what we read, what we watch, what we share - contribute to making the world a better place? Along the way, you’ll continue to develop your skills in honing and representing your fandom, specifically engaging in activities designed to help you find your fellow fans, help you find your people, and connect with them outside and beyond the course. Course-Level Learning Outcomes
* Define and describe the dynamics of geek culture (fantasy, science fiction, comic books, graphic novels), as well as its relationships to fandom, popular culture, and digital media
* Apply critical self-reflection and close reading frameworks through analytical writing and creative expression
* Engage with pop culture and fandom communities by leveraging online platforms to make connections and synthesize learning
* Reflect on your personal relationship to geek culture (fantasy, science fiction, comic books, graphic novels), and how popular culture intersects with memory and nostalgia
Course 3 Skills:
* Analysis
* Self-Reflection
* Critical Thinking
* Communication
* Culture
* Close Reading In this module, you will dig into the dynamics of comic books and geek culture and how both are rooted in the exploration of imaginary spaces (both fictional, and internal). We will introduce these topics and concepts, continue to apply our frameworks of self-reflection and close reading to them, and start preparations for the final project. 5 videos6 readings1 assignment1 discussion prompt1 plugin In this module, you will explore the contemporary evolution of the comic book superhero and their complex identity dynamics. Applying what you’ve learned about comics history and the fandom imaginary, you will encounter superheroes as characters, imaginative mirrors, and fans all at once. You will also apply your self-reflection skills to excavate your own relationship (or lack thereof) with comics and geek culture. 3 videos7 readings1 discussion prompt In this module, you will explore the darker sides of fandom and fan culture, what happens when fans turn on each other, or on outsiders, and in/out dynamics start to determine engagement and interaction. You’ll also continue applying your frameworks of analysis and reflection to shape your positive contributions to your fandom, and connect with that fandom community directly through the “Find Your Fandom” project. 4 videos5 readings1 assignment1 peer review1 discussion prompt
|
3 modules
|
Beginner level
|
12 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/comic-books-geek-culture-fandom-imaginary
| null |
930 |
How Things Work: An Introduction to Physics
|
267,583
|
4.8
| 2,929 |
Louis A. Bloomfield
|
University of Virginia
|
[]
|
An introduction to physics in the context of everyday objects. Start here! 1 video2 readings1 assignment Professor Bloomfield examines the principle of inertia through skate boarding. Objects at rest tend to remain at rest while objects in motion, tend to remain in motion. Why does a stationary skater remain stationary? Why does a moving skater tend to continue moving? How can we describe the fluid, effortless motion of a coasting skater? How does a skater start, stop, or turn? Why does a skater need ice or wheels in order to skate? Physics concepts covered include Newton's first and second laws and 5 physical quantities: position, velocity, acceleration, force, and mass. 7 videos1 assignment Professor Bloomfield examines the physics concepts of gravity, weight, constant acceleration, and projectile motion working with falling balls. 8 videos1 assignment Professor Bloomfield examines the physics concepts of Newton's third law including conserved quantities, support forces, work, energy, and mechanical advantage working with ramps. 7 videos1 assignment Professor Bloomfield illustrates the physics concepts of rotational versus translational motion, Newton's law of rotation, and 5 physical quantities: angular position, angular velocity, angular acceleration, torque, and rotational mass using seesaws. 8 videos1 assignment Professor Bloomfield illustrates the physics concept of frictional forces through experiments with wheels. 8 videos1 assignment Professor Bloomfield examines the physics concepts of momentum, impulse, angular momentum, angular impulse, and the relationship between potential energy and force using bumper cars. 7 videos1 assignment This is the final exam. 1 video1 assignment
|
8 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/how-things-work
|
96%
|
931 |
Dairy Production and Management
|
59,579
|
4.9
| 1,418 |
Alexander N. Hristov
|
The Pennsylvania State University
|
['Disease Control', 'Animal', 'Nutrition', 'Genetics']
|
With the world's first MOOOOO-C, you will gain a broad and comprehensive understanding of all aspects of dairy management such as genetics, nutrition, reproduction, animal health, farm economics, and sustainability of dairy production systems. There's something here for everyone whether you are just looking for the basics or have years of experience in the dairy industry. This is an eight-week course. Each week consists of four to nine video lectures, additional reading materials, and a multiple-choice questions quiz. Estimated study time is between three and five hours per week. Learners have the option to purchase a Course Certificate for 49.00 USD. The certificate can be purchased at any time, but you must verify your identify before taking the course quizzes in order to be eligible. For those who cannot afford the certificate fee, financial aid is available through Coursera.
Why is producing milk efficiently and sustainably so important?
Milk provides humans with over 16 essential nutrients, such as: Energy, Protein and Essential Amino acids, Vitamin A, Vitamin D, several B vitamins, including B12, Pantothenic and Folic acids, and essential minerals such as Calcium, Magnesium, Phosphorus, Potassium, Zinc, as well as other minerals. Did you know that one glass of milk provides a 5-year old child with 21% of his/her daily protein requirements and 8% of their energy needs?
Most milk in the world, about 85%, is produced from cattle. However, water buffaloes, goats, sheep, and camel are also dairy animals. The United States, India, the European Union, Brazil, and New Zealand are among the largest dairy producers in the world. Yet among these dairy-producing countries there are varied methods to generate milk with highly variable productivity and efficiency. Dairy production is vital for the survival of billions of people. Globally, around 150 million small-scale dairy households, equivalent to 750 million people, are engaged in milk production. The number and size of dairy farms varies among countries, but in India alone, there are estimated 78 million dairy farms! In the United States, one of the leading milk-producing countries in the world, total milk production has been steadily increasing in the last decades, reaching over 205 billion pounds (93 billion kilograms) in 2014. This was accompanied by a steady increase in average milk yield per cow, reaching 22,260 lb (over 10,100 kg) per lactation in 2014. How has this efficiency been achieved? What methods are necessary to ensure production of high quality milk? How do we balance milk production efficiency with animal health and environmental protection? This course will provide the student with information to better understand dairy production systems and their role in feeding the world population.
In this MOOOOO-C, you will learn about the dairy enterprise from internationally recognized dairy science professors who have delivered highly regarded dairy education programs within the United States and internationally.
Course lectures are translated into Portuguese and Chinese; PDF files of these translations can be found under each course week. The Dairy MOOC team thanks Dr. Antonio Branco (Universidade Estadual de Maringá, Brazil) and Ms. Yuanyuan Zhang (Pennsylvania State University) for translating the lecture materials.
Course Sponsors
This course was supported by the generous contributions of Innovation Center for US Dairy at Silver Level and Pancosma North America, RP Nutrients, Inc. and Arm and Hammer, which provided funding support at a Bronze Level. The Pennsylvania State University has final responsibility for the academic content of this course. In the Dairy Genetics module, you will learn about the different breeds of dairy cattle, their popularity and how performance varies from one breed to the next. We will consider the many different traits that are evaluated by farmers and breeders during genetic selection, and how we collect data to conduct genetic evaluations. In order to simplify the selection process we will consider selection indexes. You will learn how dairy cattle have changed over the last half-century, and the factors that alter the rate of genetic progress. Finally, you will learn about the technologies that have helped to accelerate genetic gain in dairy cattle such as artificial insemination and genomic testing. Those of you, who would like to get more engaged in discussions and are interested in completing the Course Certificate requirements, can participate in discussion forums and take the weekly quiz. We hope you enjoy learning about the genetics of the dairy cow! 6 videos41 readings1 assignment This week you will learn about what forages are, why they are important and the multiple roles they play on the dairy farm. We will also review some of the basic management considerations that are involved in the establishment, production and harvesting of these crops. The first lecture will focus on the multiple roles that forages play on the farm on considerations that are necessary to develop an effective forage production system. In the second lecture we will discuss some common perennial forage crops and their management. This will include alfalfa, alfalfa grass mixtures and grasses. In the third lecture, we will discuss the annual forages commonly used on dairy farms: corn, sorghums and small grains. You will learn how to utilize pastures in dairy production systems. The fourth lecture will discuss grazing and pasture management, including challenges of grazing systems, how grazing management has evolved, and proper grazing management for optimum forage and animal productivity. The fifth lecture will focus on nutrition for grazing herds, including nutrient content of pasture relative to the nutrient requirements of lactating dairy cows and strategic supplementation strategies for optimal animal health and milk production. Those of you, who would like to get more engaged in discussions and are interested in completing the Course Certificate requirements, can participate in discussion forums and take the weekly quiz. Enjoy this week's material and the entire course! 5 videos43 readings1 assignment This week you will learn about feeds commonly fed to dairy cows and feed processing. We will first discuss the feeding characteristics of forages such as corn silage, alfalfa haylage, grass and small grain silages, will then move to concentrate feeds that provide energy or protein in a dairy ration, and at the end will discuss feed additives. You will also learn about the most important factors in making high quality hay and silage for dairy cows. The final lecture of this week will introduce you to processing methods designed to increase the nutritive value of forages, the importance of particle size and effective fiber in dairy rations, and most common processing methods for cereal grains and oilseeds. At the end, we will discuss how to read and understand forage analysis reports. Those of you, who would like to get more engaged in discussions and are interested in completing the Course Certificate requirements, can participate in discussion forums and take the weekly quiz. Enjoy this week's material and the entire course! 6 videos40 readings1 assignment This week you will be introduced to the principles of animal nutrition, basic nutrients and their metabolism, sources for these nutrients in a dairy diet, the anatomy of the digestive tract of a ruminant animal, the wonderful world of the rumen microbes, and major end-product of ruminal fermentation. Further, you will learn about energy and protein metabolism and nutrition, and nutrient requirements and their importance in feeding dairy cows. In the last segment of Week 4, we will discuss the life cycle of a dairy cow, lactation curve, grouping strategies, diet formulation basics, typical sources of energy and protein in dairy diets, will touch on mineral and vitamin nutrition, summarize nutritional recommendations for the various stages of the lactation, and diet preparation techniques. Those of you, who would like to get more engaged in discussions and are interested in completing the Course Certificate requirements, can participate in discussion forums and take the weekly quiz. Enjoy this week's material and the entire course! 6 videos40 readings1 assignment Calf health, growth, and productivity rely heavily on nutrition and management practices. Every heifer calf born on a dairy farm represents an opportunity to maintain or increase herd size, to improve the herd genetically, or to improve economic returns to the farm. The objectives of raising the newborn calf to weaning age are optimizing growth and minimizing health problems. In this video we will discuss the development of the calf's digestive system, learn how important colostrum is for the immune system, and the nutrients the calf needs to be healthy and grow well. We will discuss critical phases of growth for the dairy heifer, the importance of good facilities, and how nutrition plays an important role in getting a healthy well grown heifer ready to be bred and prepared to have her first calf.Proper management and nutrition of the dairy cow transitioning into lactation is very important for obtaining a healthy calf, increased reproductive efficiency and optimal milk production in the following lactation. We will learn how this can be achieved by feeding balanced diets, providing good cow comfort, and assuring the cow is in good body condition before and after she calves. There are many feeding strategies that work for feeding dry cows however the goal should always be to provide high quality feed sources, consistent availability of feed, adequate bunk space and a comfortable environment. We will discuss how best to manage and feed the dry cow prior to calving so she can transition into lactation with a healthy calf and produce high quality milk. Those of you, who would like to get more engaged in discussions and are interested in completing the Course Certificate requirements, can participate in discussion forums and take the weekly quiz. Enjoy this week's material and the entire course! 7 videos50 readings1 assignment This week you will learn basic concepts related to reproduction on dairy farms. We will start with a discussion of the life cycle of the dairy cow and how to adequately prepare a heifer for her fist calving. Next will be a discussion of the basic anatomy and function of the male and female reproductive tracts. This will be followed by an overview of the bovine estrous cycle and the main hormones and ovarian structures that control the cycle. We will follow this with a discussion of factors controlling the expression of estrus by dairy cows and how to be more effective at detecting estrus. We will highlight the critical need to time ovulation and insemination to maximize conception rates and will discuss some of the factors which reduce conception rates. This will be illustrated by a discussion of the key reproductive metric, pregnancy rate. Viewers will learn about strategies to increase pregnancy rates and will better understand methods used for pregnancy detection along with the critical need for early and accurate pregnancy detection to maximize the farms’ pregnancy rates. Those of you, who would like to get more engaged in discussions and are interested in completing the Course Certificate requirements, can participate in discussion forums and take the weekly quiz. Enjoy this week's material and the entire course! 6 videos39 readings1 assignment In Week 7 of this course, you will learn about disease concerns of dairy cows and calves and management practices addressing diagnosis and prevention. Our discussions will progress from first establishing disease prevention concepts of biosecurity and evolutionary change to dairy herd health programs. The next three discussions will focus on disease issues related to the calving cow, calf and lactating cow. These lessons will provide background information and practical skills in recognizing disease problems early in an effort to minimize adverse consequences on animal health and performance. The last two discussions will focus on disease treatment and prevention practices in addressing important conceptual approaches as specific mechanisms for treatment and prevention are dependent upon regulatory issues within a given country. We will address the controversial issue of antibiotic usage in the treatment of cows as an important concern for food production, but also as part of good animal care and ensuring animal welfare. Preventive practices of vaccination strategies and parasite control will be framed in a conceptual approach that could be applied to differing farm situations. Finally our discussion will emphasize the importance of good nutrition, thus linking information from other course modules, to establishing proper dairy management practices to ensuring quality cow care and minimizing disease risks. Those of you, who would like to get more engaged in discussions and are interested in completing the Course Certificate requirements, can participate in discussion forums and take the weekly quiz. Enjoy this week's material and the entire course! 13 videos81 readings1 assignment In Week 8 of the course, you will learn about the basics of dairy farm management and identify some key aspects of farm level economics that impact farm productivity and profitability. From crops to cows to cash, the dairy farm is an economic engine that has positive impacts on local communities. The second part of this series expands on dairy’s local impact to provide a global view of dairy markets around the world. From price volatility to seasonal milk supplies, the world marketplace for dairy products is complex. In the last lectures of this course we will discuss the environmental implications of dairy production and strategies for decreasing nitrogen, phosphorus, and greenhouse gas emissions from dairy operations. Those of you, who would like to get more engaged in discussions and are interested in completing the Course Certificate requirements, can participate in discussion forums and take the weekly quiz. Enjoy this week's material and the entire course! 7 videos51 readings1 assignment
|
8 modules
| null |
75 hours to complete (3 weeks at 25 hours a week)
|
https://www.coursera.org/learn/dairy-production
|
98%
|
932 |
Machine Learning: an overview
|
4,922
|
4.6
| 103 |
Marcello Restelli
|
Politecnico di Milano
|
[]
|
The course provides a general overview of the main methods in the machine learning field. Starting from a taxonomy of the different problems that can be solved through machine learning techniques, the course briefly presents some algorithmic solutions, highlighting when they can be successful, but also their limitations. These concepts will be explained through examples and case studies. 4 videos1 assignment 3 videos1 assignment 3 videos1 assignment
|
3 modules
|
Beginner level
|
2 hours to complete
|
https://www.coursera.org/learn/machine-learning-overview
| null |
933 |
Digital Marketing Analytics in Practice
|
126,940
|
4.5
| 3,300 |
Kevin Hartman
|
University of Illinois Urbana-Champaign
|
['Analytics', 'Digital Marketing', 'Marketing Analytics', 'Marketing Performance']
|
Successfully marketing brands today requires a well-balanced blend of art and science. This course introduces students to the science of web analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide the foundation needed to apply data analytics to real-world challenges marketers confront daily. Digital Analytics for Marketing Professionals: Marketing Analytics in Practice is the second in a two-part series of complementary courses and focuses on the skills and practical abilities analysts need to be successful in today's digital business world. You will be able to:
- Identify the web analytic tool right for your specific needs
- Understand valid and reliable ways to collect, analyze, and visualize data from the web
- Utilize data in decision making for agencies, organizations, or clients
This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/. In the orientation, you will become familiar with the course, your instructor, your classmates, and our learning environment. The orientation also helps you obtain the technical skills required for the course. Every analyst dreams of coming up with the “big idea” – the game-changing and previously unseen insight or approach that gives their organization a competitive advantage and their career a huge boost. But dreaming won’t get you there. It requires a thoughtful and disciplined approach to analysis projects. In this part of the course, I detail the four elements of the Marketing Analytics Process (MAP): plan, collect, analyze, report. Module 1 also explains the role of the analyst, the six mutually exclusive and collectively exhaustive (“MECE”) marketing objectives of analytics, how to find context and patterns in collected data, and how to avoid the pitfalls of bias. 9 videos8 readings7 quizzes1 peer review In Module 2, we dive headlong into the most important aspect of digital marketing analytics: transforming the data the analyst compiled into a comprehensive, coherent, and meaningful report. I outline the key characteristics of good visuals and the minutiae of chart design and provide a five-step process for analysts to follow when they’re on their feet and presenting to an audience. The goal is to equip analysts with the tools they need to tell a compelling and memorable story that “cuts through the noise” of the overwhelming amount of information audiences experience every day. 6 videos2 readings6 quizzes1 peer review Module 3 brings to life the concepts, theories, techniques, and tools discussed in the course in a business case written about Bellabeat, a high-tech design and manufacturing company that produced health-focused smart devices for women. Students will see each step in the MAP illustrated through the case. 5 videos2 readings5 quizzes1 peer review Data’s road from crude maps to gigabytes of multidimensional information has been a long and winding one. But it is far from over. If anything, the industry finds itself at a critical crossroads that will determine its future for decades to come. Module 4 explores this predicament while casting an eye toward what comes next for digital marketing analytics. 5 videos4 readings5 quizzes1 peer review1 plugin
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/digital-analytics
|
97%
|
934 |
The Kennedy Half Century
|
26,620
|
4.7
| 495 |
Professor Larry J. Sabato
|
University of Virginia
|
[]
|
When John F. Kennedy entered the presidential limousine at Love Field in Dallas, Texas on November 22, 1963, he began his ride into history. That journey continues even today and we call it the Kennedy legacy. This course will explore the Presidency, assassination, and lasting legacy of President John F. Kennedy. Students will learn how JFK’s life, administration, and tragic death have influenced the general public, the media, and each of the nine U.S. presidents who followed.
Understanding the Kennedy legacy and being able to identify elements of his legacy within the context of modern politics helps understand many of the vexing problems that developed over the last half century as well as many of the challenges that confront us today.
November 22, 1963 was so powerful a moment that in the fifty years since the assassination, every U.S. President that followed JFK has used Kennedy’s words and actions in an effort to craft their own political image. Why does Kennedy’s influence persist, and will it continue? What are the effects?
We’ll address these questions and more as we explore The Kennedy Half Century.
Follow on Twitter: @JFKclass. 9 videos 11 videos1 reading 13 videos 11 videos1 assignment
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/kennedy
|
97%
|
935 |
Core 2: OS, Software, Security and Operational Procedures
|
2,502
|
4.7
| 30 |
IBM Skills Network Team
|
IBM
|
['Technical Support', 'security', 'Operating Systems', 'IT Troubleshooting', 'Mobile Devices']
|
Are you interested in becoming a proficient and sought-after IT professional? Are you currently or do you plan to pursue a career in an IT support, network technician, or other IT-related role? This IBM course, designed for individuals with IT Fundamentals knowledge, is part of a series of courses that will help you prepare for the CompTIA Core 2 Certification exam. You will gain a solid foundation in operating systems, IT support best practices and procedures, and the skills necessary to excel in an IT role. You will delve into the world of operating systems, exploring the editions of Microsoft Windows, Apple macOS, and Linux. You will gain a solid understanding of these OS installation and update processes and practical insights into their unique features and functionalities.
With hands-on labs and activities, you will learn to navigate and use standard features and commands across various OSs, discover the power of command line and console tools, and explore security measures, including firewall configuration, SOHO router security, and data destruction to ensure the security of networks and mobile devices.
Through instructional readings and videos, you will be introduced to fundamental IT support best practices, how to diagnose and troubleshoot common PC, mobile, and security issues, and how to mitigate the impact of malware on systems and networks. This course uniquely blends theory with practical labs and activities, preparing you to excel in your IT support role. This module will teach you about Microsoft Windows operating system (OS) editions and Windows management features.
Lesson 1 introduces the process and benefits of installing and updating a Windows OS. You will learn the importance of partitioning and drive formatting, the features offered by Windows 10, 11, and Server OS editions, and you will get hands-on experience exploring Windows Server features.
In Lesson 2, you will explore the Windows Command Prompt Tool features for administration purposes, and you’ll be able to use the Windows commands you learn in a hands-on lab. You’ll also learn about system utility applications, the Microsoft Management Console, and some of its snap-in tools. 8 videos2 readings3 assignments2 app items6 plugins In this module, you will learn how to manage operating systems such as Linux and macOS and utilize many of their features to enhance your operating system management experience. In Lesson 1, you will explore different aspects of the Linux operating system. You will learn how to install these systems and how to upgrade them. Learn how to use the terminal window, navigate and work with the OS using it. Additionally, you will learn about the versatility of Samba, a network protocol that promotes collaboration across Linux and Windows environments. Whereas lesson one focused on Linux, lesson two focuses primarily on macOS and mobile device operating systems, Android and iOS. You will learn about features unique to macOS, how to upgrade it, and how to configure its preferences. 11 videos1 reading3 assignments2 app items7 plugins In this module, you will learn about security for mobile devices and home networks. Lesson One focuses on Microsoft Windows security best practices, such as using its Active Directory for managing administrative tasks, authentication methods, important security settings, and Windows user management and permissions administration. You will also learn about anti-malware tools and how to configure firewalls to prohibit unwanted users from accessing the systems on the network. Lesson Two engages you in securing small and home office routers as well as mobile devices. You learn about wireless encryption, managing security on SOHO routers and SOHO networks, hardening devices, and mobile device protection. 9 videos1 reading3 assignments4 app items7 plugins In this module, you will learn how to troubleshoot common Windows OS as well as mobile OS problems and security issues.
Lesson One focuses on common Windows OS problems. You’ll learn about startup problems, security issues, malware, and the best practices that can help you avoid them.
Lesson Two focuses on common mobile OS and application problems. You’ll find out about the security issues that affect the applications and OS of your mobile device and what you can do to keep your mobile device secure. 7 videos1 reading3 assignments2 app items6 plugins This module will teach you different operational procedures, from managing network infrastructure to material safety and handling in an information technology space.
Lesson 1 will teach you the best asset and change management practices. This lesson will introduce you to new types of documentation and ticketing systems. Hands-on labs allow you to gain hands-on experience locating manufacturing specifications for component repair and how to onboard new users.
In Lesson 2, you will explore the best practices for having a safe environment in an information technology space. You will also learn the environmental impacts of disposing of IT equipment and the proper material handling procedures. A practice quiz will demonstrate what you have learned about safety protocols.
Lesson 3 will test your knowledge of what you have learned about operational procedures in a graded quiz. 6 videos1 reading3 assignments1 app item4 plugins In this module, you will test your knowledge and skills acquired in this course. This module contains a 20-question graded final exam focused on the content of this course. You may also choose to complete an (optional) Honors project where you can apply your new skills gained in the previous modules. You will examine three realistic scenarios that simulate common issues that may arise in troubleshooting software, security, and operational procedures. 2 readings4 assignments3 app items4 plugins
|
6 modules
|
Intermediate level
|
26 hours to complete (3 weeks at 8 hours a week)
|
https://www.coursera.org/learn/core2-os-software-security-and-operational-procedures
| null |
936 |
Data Analysis with Python Specialization
|
Enrollment number not found
|
4.8
| 11 |
Di Wu
|
University of Colorado Boulder
|
['Data Clustering Algorithms', 'Dimensionality Reduction', 'K-Means Clustering', 'Principal Component Analysis (PCA)', 'Dbscan', 'Ensemble Learning', 'Linear Regression', 'Cross Validation', 'regression', 'Scikit-Learn', 'Data Clustering Algorithms', 'Dimensionality Reduction', 'K-Means Clustering', 'Principal Component Analysis (PCA)', 'Dbscan', 'Ensemble Learning', 'Linear Regression', 'Cross Validation', 'regression', 'Scikit-Learn']
|
The Data Analysis specialization will provide a comprehensive overview of various techniques for analyzing data. The courses will cover a wide range of topics, including Classification, Regression, Clustering, Dimension Reduction, and Association Rules. The courses will be very hands-on and will include real-life examples and case studies, which will help students develop a deeper understanding of Data Analysis concepts and techniques. The courses will culminate in a project that demonstrates the student's mastery of Data Analysis techniques. Applied Learning Project The "Data Analysis Project" course empowers students to apply their knowledge and skills gained in this specialization to conduct a real-life data analysis project of their interest. Participants will explore various directions in data analysis, including supervised and unsupervised learning, regression, clustering, dimension reduction, association rules, and outlier detection. Throughout the modules, students will learn essential data analysis techniques and methodologies and embark on a journey from raw data to knowledge and intelligence. By completing the course, students will be proficient in data analysis, capable of applying their expertise in diverse projects and making data-driven decisions. Understand the concept and significance of classification as a supervised learning method. Identify and describe different classifiers, apply each classifier to perform binary and multiclass classification tasks on diverse datasets. Evaluate the performance of classifiers, select and fine-tune classifiers based on dataset characteristics and learning requirements. Understand the principles and significance of regression analysis in supervised learning. Implement cross-validation methods to assess model performance and optimize hyperparameters. Comprehend ensemble methods (bagging, boosting, and stacking) and their role in enhancing regression model accuracy. Understand the principles and significance of unsupervised learning, particularly clustering and dimension reduction. Apply clustering techniques to diverse datasets for pattern discovery and data exploration. Implement Principal Component Analysis (PCA) for dimension reduction and interpret the reduced feature space. Understand the principles and significance of unsupervised learning methods, specifically association rules and outlier detection Grasp the concepts and applications of frequent patterns and association rules in discovering interesting relationships between items. Apply various outlier detection methods, including statistical and distance-based approaches, to identify anomalous data points. Define the scope and direction of a data analysis project, identifying appropriate techniques and methodologies for achieving project objectives. Apply various classification and regression algorithms and implement cross-validation and ensemble techniques to enhance the performance of models. Apply various clustering, dimension reduction association rule mining, and outlier detection algorithms for unsupervised learning models.
|
5 course series
|
Intermediate level
|
2 months (at 10 hours a week)
|
https://www.coursera.org/specializations/data-analysis-python
| null |
937 |
Marketing Analytics Foundation
|
84,229
|
4.8
| 1,968 |
Anke Audenaert
|
Meta
|
['Data Analysis', 'Marketing', 'Digital Marketing', 'Marketing Analytics']
|
This course lays the foundation of marketing analytics. You’ll learn the basic principles of marketing, the role data analysis plays in digital marketing and how data is collected and managed. By the end of this course you will be able to:
• Describe how marketers use data to inform campaign decisions
• Describe the basic principles of marketing
• Identify why data analysis matters in digital marketing
• Implement the Meta pixel to capture data used to track visitor activity on a website
• Explain how an API connects data captured offline to an online platform
• Describe common platforms for online data management and evaluation
• Navigate Google Analytics and Meta Ads Manager reports
• Explain the significance of the privacy regulations that govern the online marketing space
Regardless of your current marketing and analytics experience, this course will help you build a solid foundation for incorporating data into your marketing efforts.
Learners should have basic internet navigation skills and be eager to participate. This week you will learn the importance of data and analytics in marketing and how they inform marketing decisions. You’ll also be briefly introduced to basic marketing principles. 16 videos5 readings3 assignments In week 2 you will gain an understanding of how data is collected and used in digital marketing. You will learn the difference between first, second and third party data and will get an overview of the Facebook pixel and its use. 15 videos2 readings3 assignments This week you will learn how spreadsheets are used to visualize and analyze data for marketing. You will be introduced to Google Analytics and Facebook Ads Manager and how these tools are used to provide data for marketers to analyze. 12 videos4 readings9 assignments In the final week you will learn about the regulations around gathering and using online data and consumer’s rights. 11 videos2 readings3 assignments1 discussion prompt
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/marketing-analytics-foundation
|
98%
|
938 |
Intermediate Object-Oriented Programming for Unity Games
|
18,247
|
4.6
| 320 |
Dr. Tim "Dr. T" Chamillard
|
University of Colorado System
|
[]
|
This course is the fourth course in the specialization about learning how to develop video games using the C# programming language and the Unity game engine on Windows or Mac. Why use C# and Unity instead of some other language and game engine? Well, C# is a really good language for learning how to program and then programming professionally. Also, the Unity game engine is very popular with indie game developers; Unity games were downloaded 16,000,000,000 times in 2016! Finally, C# is one of the programming languages you can use in the Unity environment. This course assumes you have the prerequisite knowledge from the previous three courses in the specialization. You should make sure you have that knowledge, either by taking those previous courses or from personal experience, before tackling this course. Throughout this course you'll build on your foundational C# and Unity knowledge by developing more robust games with better object-oriented designs using file input and output, inheritance and polymorphism, and event handling.
This course gives you even more tools to help you build great games with C# and Unity!
Module 1: Start using files to implement your Unity games
Module 2: Learn how inheritance and polymorphism help us write less code for our games
Module 3: Implement event handling to make better object-oriented designs and add menus to your Unity games
Module 4: Explore the complete implementation of a small Unity game
“Unity” is a trademark or registered trademark of Unity Technologies or its affiliates in the U.S. and elsewhere.
This course is an independent work and is not sponsored by, authorized by, or affiliated with Unity Technologies or its affiliates 12 videos10 readings1 programming assignment1 discussion prompt 13 videos5 readings1 programming assignment1 discussion prompt 10 videos4 readings1 programming assignment1 discussion prompt 10 videos2 readings1 programming assignment1 discussion prompt Please read the Supplemental Material reading in Week 1. I've included the material in this module for those learners who might have missed it based on the course and Specialization they were currently enrolled in when the new versions of the courses and the new version of the Specialization went live. There's nothing graded in this module, the materials are just provided here so nobody misses any of the great stuff in the Specialization! Note that the exercise and programming assignment numbers are from a different course and have nothing to do with the exercise and programming assignment numbers listed in the four "real" weeks of this course. 28 videos15 readings4 programming assignments
|
5 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/intermediate-object-oriented-programming-unity-games
|
93%
|
939 |
Academic Discussions in English
|
33,403
|
4.6
| 124 |
Tamy Chapman
|
University of California, Irvine
|
[]
|
This is the third course in the Learn English: Advanced Speaking and Listening specialization. In this class you will learn about different types of conversations you will have in academic settings. You will also learn some strategies for helping you understand other people's meaning and for helping you express yourself effectively. Learners will record several videos of themselves participating in assigned group discussions with their own friends and upload the videos for peer feedback. While this might seem intimidating, it will be a great opportunity for you to practice and improve your discussion skills. Please note that the free version of this class gives you access to all of the instructional videos and handouts. The peer feedback and quizzes are only available in the paid version. This is the third course in the Learn English: Advanced Speaking and Listening specialization. In this class you will learn about different types of conversations you will have in academic settings. You will also learn some strategies for helping you understand other people's meaning and for helping you express yourself effectively. This first module will show you the importance of effective academic conversational English. You'll see how it is different from other conversational English and why it is necessary to make you successful in college environments. Finally, you'll do a video assignment in which you record yourself in a group discussion. You'll submit this video for feedback on your discussion techniques. 7 videos6 readings4 assignments2 peer reviews2 discussion prompts This week, you'll learn about the importance of elaborating in a conversation and learn to avoid some common problems that occur when elaboration doesn't happen. You'll learn several ways to add examples to your discussions and how to use critical thinking to take make your discussions go deeper. Again, you will have the chance to practice having a group discussion and to submit a video of it for feedback. 4 videos5 readings4 assignments1 peer review1 discussion prompt Now, you'll learn how to maintain a smooth discussion by avoiding common problems with interaction and participation. You'll also learn how to listen to other speakers' ideas and learn how to agree or disagree with others in your discussion. Once again, you will be able to practice having a group discussion, and you will record and share the video with other learners. 3 videos4 readings5 assignments1 peer review1 discussion prompt In the final week, you will learn how to synthesize the ideas in your discussions and how to come up with meaningful take-aways and action points. You'll also learn how to reflect on the important points in a discussion so that the whole thing is meaningful. You will get one more chance to demonstrate your discussion skills and get feedback by sharing a video of your discussion. 3 videos5 readings4 assignments2 peer reviews1 discussion prompt
|
4 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/academic-discussion-english
|
96%
|
940 |
Gemini for Google Workspace Specialization
|
Enrollment number not found
|
4.6
| 13 |
Google Cloud Training
|
Google Cloud
|
['Business Communication', 'Generative AI', 'Project Management', 'Generative AI', 'Writing', 'Collaboration', 'Business Communication', 'Generative AI', 'Project Management', 'Generative AI', 'Writing', 'Collaboration']
|
This specialization introduces learners to Gemini for Google Workspace, an add-on that provides users with generative AI features in Google Workspace. Using a combination of presentations and hands-on activities, you learn about the key features of Gemini including how to: Write and refine a draft in Docs. Draft and refine emails in Gmail. Generate custom visuals in Slides. Create a project tracker in Sheets. Express yourself on calls in Meet. Summarize files, search for content, and synthesize information. Applied Learning Project Projects challenge students to solve business problems using Gmail, Google Docs, Google Slides, Google Sheets, and Google Meet. Note:We recommend that students engage with this content using a Chromebook, Windows, or Mac OS computer with Google Chrome installed. Additionally, students need a Google Workspace account with access to the Gemini for Google Workspace add-on. Define Generative AI and understand its potential, challenges, and limitations. Outline the main features in the Gemini Enterprise add-on. Understand how to use Gemini responsibly. Use AI to write a new email draft. Use AI to refine an email draft. Use Gemini to generate written content. Use Gemini to refine written content. Proofread your document for spelling, grammar, style, and word choice by using Gemini. Use Gemini to generate images in a presentation. Use Gemini to add a style to your image. Use Gemini to create project plans and trackers. Edit prompts to create new versions of tables. Create meeting backgrounds using Gemini. Use Gemini to enhance your video quality during a meeting. Use translated captions with Gemini. Generate a discussion summary an action items using "Take notes for me" in Google Meet. Describe the high-level features of Gemini in Drive. Use Gemini in Drive to search for and ask questions about an individual file. Formulate broader, topic-based prompts to elicit desired responses from Gemini. Synthesize relevant information across Google Workspace and Google web searches using Gemini.
|
7 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/gemini-for-google-workspace
| null |
941 |
How to Build an Executive Presence
|
Enrollment number not found
|
4.4
| 18 |
Anya Soto
|
Coursera Instructor Network
|
['Authentic Executive Presence Development', 'Strategic Relationship Management', 'ROI Maximization', 'Effective Collaboration', 'Self-Reflection and Self-Improvement']
|
This course is designed to equip learners with knowledge and concepts around building a powerful executive presence while finding the balance between self-promotion and genuine contribution, asserting your presence and collaborating effectively with others. I will share with you how After coaching executives for the past 15 years and spending time with hundreds of CEO's as a Vistage presenter, I can help you stand out without creating a perception of self-serving motives or overshadowing team contributions. Would you like to learn how to be seen for the right reasons, in the right way, at the right time and by the right people?
This course is designed for aspiring leaders, mid-level managers, senior executives, entrepreneurs, and professionals seeking to enhance their professional growth and impact. It offers practical strategies to develop an executive presence that balances authority with authenticity, empowering participants to stand out and lead effectively in any professional setting.
Interest in professional development and willingness to learn and apply new skills and concepts. Desire to enhance executive presence and openness to feedback and self-improvement through self-reflection and exercises.
After completing this course, learners will be able to analyze and cultivate their authentic executive presence, maximizing their Return on Investment (ROI). They will also demonstrate proficiency in strategically managing relationships and devising a personalized journey map for their strategic executive presence development. This course is designed to equip learners with knowledge and concepts around building a powerful executive presence while finding the balance between self-promotion and genuine contribution, asserting your presence and collaborating effectively with others. 12 videos4 readings1 assignment2 discussion prompts
|
1 module
|
Beginner level
|
1 hour to complete
|
https://www.coursera.org/learn/how-to-build-an-executive-presence
| null |
942 |
Preventing Chronic Pain: A Human Systems Approach
|
36,468
|
4.7
| 413 |
Dr. James Fricton, DDS, MS
|
University of Minnesota
|
['Chronic Pain Management', 'Plan', 'Pain Management', 'Opiod Addiction And Abuse Treatment']
|
Chronic pain is at epidemic levels and has become the highest-cost condition in health care. This course uses evidence-based science with creative and experiential learning to better understand chronic pain conditions and how they can be prevented through self-management in our cognitive, behavioral, physical, emotional, spiritual, social, and environmental realms. The goal of this course is to blend creative, experiential, and evidence-based teaching strategies to help participants understand chronic pain conditions and how a human systems approach can be applied to self-management strategies to reduce risk factors, enhance protective factors, and prevent chronic pain. There are four major objectives to the course;
1. Describe the prevalence, personal impact, and health care dilemma associated with chronic pain.
2. Recognize the clinical characteristics and underlying etiology of several common pain conditions and the peripheral, central, and genetic mechanisms of chronic pain
3. Based on the literature associated with risk and protective factors in the seven realms of our lives, learn specific strategies in each realm that can be employed daily to prevent chronic pain and enhance wellness.
4. Appreciate the value of a human systems approach to health care and how it can provide a basis for integrative, interdisciplinary, and individualized care to preventing pain and enhancing wellness.
CONTINUING EDUCATION CREDIT
Health Care Professionals
Health care professionals who participate in this CE activity may submit this certificate statement of participation to their appropriate accrediting organizations or state boards for consideration of credit. The participant is responsible for determining whether this activity meets the requirements for acceptable continuing education. Email your Coursera certificate statement of completion to your appropriate organization. In this first module, we will introduce you to the course and present an overview of the topics to be discussed and format of the course. We will also present information about receiving Continuing Education, joining the International Myopain Society, and supporting the Campaign for Preventing Chronic Pain 7 videos6 readings1 assignment2 discussion prompts 14 videos3 readings2 assignments2 discussion prompts 12 videos4 readings2 assignments2 discussion prompts 14 videos3 readings2 assignments2 discussion prompts 9 videos2 readings2 assignments2 discussion prompts 12 videos3 readings2 assignments2 discussion prompts 10 videos3 readings2 assignments2 discussion prompts 14 videos3 readings2 assignments2 discussion prompts 13 videos3 readings2 assignments2 discussion prompts 20 videos4 readings1 assignment2 discussion prompts
|
10 modules
|
Beginner level
| null |
https://www.coursera.org/learn/chronic-pain
|
97%
|
943 |
HPE Aruba Networking Management Techniques
|
1,827
|
4.7
| 14 |
HPE Aruba Education Services
|
HPE Aruba Networking
|
['Network Planning And Design', 'Network Monitoring']
|
This 2-part eLearning course builds an understanding of modern cloud-network design and management techniques, crystalizing lofty ideas of "cloud" and "edge" so you can embrace the latest industry trends and best-practices. A successful modern network architect requires a keen understanding of business requirements, network components, and the challenges of architecting good solutions. In the 1-hour Aruba Modern Cloud Network Design course you’ll get a high level overview of key network design topics trending in the Edge era.
The devices we manage constantly evolve as new protocols, security mechanisms, and redundancy solutions emerge; and so the techniques we use to manage these dynamic systems must respond to and even anticipate this changing landscape. In the Modern Cloud Network Management Techniques 1-hour course you’ll learn about key aspects of the network management journey and the newer technologies and techniques to help you embrace the Edge. Learn about the network management challenges that drive new technologies, get familiar with classic Network Management System (NMS) tools, and learn about the modern NMS tools like Aruba ESP developed to reduce overhead, speed diagnosis, and improve situational awareness.
Typical candidates for this course are IT Professionals and/or Network Engineers who want to learn about Aruba’s modern approach to network design. In the Modern Campus Network Management Techniques 1-hour course you’ll learn about key aspects of the network management journey and the newer technologies and techniques to help you embrace the Edge. Learn about the network management challenges that drive new technologies, get familiar with classic Network Management System (NMS) tools, and learn about the modern NMS tools like Aruba ESP developed to reduce overhead, speed diagnosis, and improve situational awareness. 5 videos1 assignment
|
1 module
|
Intermediate level
|
1 hour to complete
|
https://www.coursera.org/learn/cloud-based-network-design-and-management
| null |
944 |
Financial Accounting: Advanced Topics
|
57,068
|
4.7
| 1,687 |
Oktay Urcan
|
University of Illinois Urbana-Champaign
|
['Cash Flow', 'Financial Accounting', 'Cash Flow Statement', 'Financial Statement']
|
In this course, you will explore advanced topics in financial accounting. You will start your journey with accounting for assets with more than a 1-year life. You will learn in detail how firms account for fixed assets. You will then move on to the financing of assets and discuss accounting for liabilities. The course will continue with an in-depth exploration of shareholders’ equity. Finally, you will critically evaluate the preparation, components, and analysis of the cash flows statement. Upon successful completion of this course, you will be able to
• account for fixed assets,
• understand accounting for liabilities,
• evaluate shareholders’ equity section of a balance sheet, and
• understand preparation and information provided by cash flows statement.
This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu. You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course. 2 videos5 readings1 quiz1 discussion prompt1 plugin Long-term assets, assets that can be converted into cash in a time period of more than 1 year, constitute a large portion of a balance sheet for a lot of public companies. Understanding accounting for long-term assets will help you uncover how these accounts change over time, their valuation, and their usefulness in managerial decision making. 7 videos5 readings7 quizzes One of the major sources of financing for many firms is liabilities. Firms routinely finance their operations through various liabilities, including accounts payable, bank loans, and bonds. Accounting for liabilities will help you understand how liabilities are created, how they are valued, and how they inform a firm’s liquidity position. 7 videos4 readings5 quizzes1 assignment One of the major sources of financing for many firms is contributions from shareholders. The shareholders’ equity section of a balance sheet shows details of the investments of shareholders. Accounting for shareholders’ equity will help you understand the amount of shareholder investment, the number of shares issued in return by the firm for shareholders, the amount of earnings earned by the firm but not distributed to shareholders, and information about the amount of shares repurchased by the firm from the stock market. 6 videos5 readings6 quizzes One of the major financial statements is cash flows statement. This statement describes in detail how cash changes for a firm over a certain period. The cash flows statement provides valuable information about the liquidity position of a firm, the cash consequences of managerial operating and investing decisions, as well as the earnings quality of a firm. 5 videos6 readings3 quizzes1 assignment1 peer review1 plugin
|
5 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/financial-accounting-advanced
|
97%
|
945 |
Introduction to Embedded Machine Learning
|
45,953
|
4.8
| 663 |
Shawn Hymel
|
Edge Impulse
|
['Computer Programming', 'Arduino', 'Machine Learning', 'Microcontroller', 'Embedded System Design']
|
Machine learning (ML) allows us to teach computers to make predictions and decisions based on data and learn from experiences. In recent years, incredible optimizations have been made to machine learning algorithms, software frameworks, and embedded hardware. Thanks to this, running deep neural networks and other complex machine learning algorithms is possible on low-power devices like microcontrollers. This course will give you a broad overview of how machine learning works, how to train neural networks, and how to deploy those networks to microcontrollers, which is known as embedded machine learning or TinyML. You do not need any prior machine learning knowledge to take this course. Familiarity with Arduino and microcontrollers is advised to understand some topics as well as to tackle the projects. Some math (reading plots, arithmetic, algebra) is also required for quizzes and projects.
We will cover the concepts and vocabulary necessary to understand the fundamentals of machine learning as well as provide demonstrations and projects to give you hands-on experience. In this module, we will introduce the concept of machine learning, how it can be used to solve problems, and its limitations. We will also cover how machine learning on embedded systems, such as single board computers and microcontrollers, can be effectively used to solve problems and create new types of computer interfaces. Then, we will introduce the Edge Impulse tool and collect motion data for a "magic wand" demo. Finally, we will examine the various features that can be calculated from this raw motion data, including root mean square (RMS), Fourier transform, and power spectral density (PSD). 13 videos15 readings5 assignments2 discussion prompts In this module, we will look at how neural networks work, how to train them, and how to use them to perform inference in an embedded system. We will continue the previous demo of creating a motion classification system using motion data collected from a smartphone or Arduino board. Finally, we will challenge you with a new motion classification project where you will have the opportunity to implement the concepts learning in this module and the previous module. 10 videos10 readings5 assignments1 discussion prompt In this module, we cover audio classification on embedded systems. Specifically, we will go over the basics of extracting mel-frequency cepstral coefficients (MFCCs) as features from recorded audio, training a convolutional neural network (CNN) and deploying that neural network to a microcontroller. Additionally, we dive into some of the implementation strategies on embedded systems and talk about how machine learning compares to sensor fusion. 9 videos7 readings4 assignments1 discussion prompt1 plugin
|
3 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/introduction-to-embedded-machine-learning
|
96%
|
946 |
Real-Time Embedded Systems Theory and Analysis
|
5,969
|
4.3
| 15 |
Sam Siewert
|
University of Colorado Boulder
|
['Dynamic and Static Scheduling Policies', 'Priority Ceiling Protocol', 'Rate Monotonic Theory', 'EDF (Earliest Deadline First)', 'Priority Inheritance Protocol']
|
This course can also be taken for academic credit as ECEA 5316, part of CU Boulder’s Master of Science in Electrical Engineering degree. This course provides an in-depth and full mathematical derivation and review of models for scheduling policies and feasibility determination by hand and with rate monotonic tools along with comparison to actual performance for real-time scheduled threads running on a native Linux system. By the end of this course the learner will be able to full derive the fixed priority rate monotonic least upper bound for feasibility as well as justifying the rate monotonic policy and will be able to compare to dynamic priority scheduling including earliest deadline first and least laxity policies.
At the end of this course learners will be able to fully derive and explain the math model for the rate monotonic least upper bound as well as performing timing diagram analysis for fixed and dynamic priority software services. Tools to provide analysis will be learned (Cheddar) to automate timing analysis and to compare to actual performance.
Specific objectives include:
● Rate monotonic theory (complete math models)
● Differences between fixed priority rate monotonic policy and dynamic priority earliest deadline first and least laxity policies
● Scheduling theory and practice writing code for multi-frequency executives, priority preemptive RTOS services, and real-time threaded services on traditional operating systems (Linux)
● Building a simple Linux multi-service system using POSIX real-time extensions on Raspberry Pi 3b using sequencing and methods to log and verify agreement between theory and practice
● Timing diagram generation and analysis using Cheddar At the end of this module, you will be able to analyze the mathematics involved in Rate Monotonic Least Upper Bound Condition along with its challenges and alternatives to it. An extension to RM scheduling policy i.e. Deadline Monotonic Scheduling Policy along with implementation of completion test for determining exact feasibility for Rate Monotonic Scheduling policy is also in scope of this module. Working on Programming assignments will give system level implementation of real time services and determining the best scheduling policies for meeting the deadlines for the designed real-time systems along with their trade offs. 14 videos3 readings1 quiz3 programming assignments3 peer reviews1 discussion prompt At the end of this module learners will be able to describe the design pattern for real-time services, describe implementation challenges such as unbounded blocking and describe normal operation - request for service synchronization between an ISR and each thread or task, initialization, keep-alive posting, error handling, and termination. 15 videos2 readings1 quiz3 programming assignments3 peer reviews At the end of this Module learners will know when to use dynamic priority policies, advantages of them for soft real-time, disadvantages for error detection and recovery, challenges of feasibility determination and efficiency compared to fixed priority. 6 videos1 reading1 quiz1 programming assignment1 peer review At the end of this Module learners will be able to describe issues with resources used beyond CPU (memory, I/O, and storage) and how to avoid problems or recover from them 12 videos1 reading1 quiz2 peer reviews
|
4 modules
|
Advanced level
| null |
https://www.coursera.org/learn/real-time-embedded-theory-analysis
| null |
947 |
Anti-Racism I
|
27,035
|
4.6
| 266 |
Shawn
|
University of Colorado Boulder
|
['History of Race and Racism', 'anti-racism', 'Talking about Race and Racism', 'Identity', 'Anti-Racism Terms']
|
Anti-Racism I is an introduction to the topic of race and racism in the United States. The primary audience for this course is anyone who is interested in learning about race/racism in the US who has never taken a course in critical race or ethnic studies or affiliated fields (indeed, who may not know what the fields of critical race studies or ethnic studies are), who has never read a book about race/racism, or attended any race equity or diversity trainings on the topic of race/racism. In this course you will learn how to:
- Use and comprehend contemporary intersectional terminology through a provided glossary
- Critically discuss “whiteness”
- Recognize the concept of White privilege that all White people have whether they want that privilege or not and to differentiate between White supremacy as a systemic concept vs. White supremacists (who are professional racists like the KKK).
- Distinguish between being not racist and being anti-racist
- Define systemic and institutional racism
- Accept the unequal history of race and racism in the United States that has created racial hierarchies that has disenfranchised Black Americans
- Share with others the true foundations of United States’s histories beginning with the acknowledgement of settler colonialism and the rewards that White people have received due to White supremacy and Black oppression.
- Talk about race and racism
- Explain why phrases like “All Lives Matter” and “Blue Lives Matter” are racist
- Recognize that anyone can be anti-racist--it only takes the dedication and decision to be anti-racist, to educate yourself about the history of racism in the US and then to talk in an anti-racist way and to act as an anti-racist
Course logo image credit: Liam Edwards, 06/04/2021. Available on Unsplash at https://unsplash.com/photos/x15GAQNepcQ This week you will learn various ways of defining race through definitions of whiteness. While race and racism have, in popular discourse, been understood to refer to non-white people, we start with whiteness since whiteness has been the primary ideology that dominated the formation of the United States, its laws, power structure, society, and culture. The anti-racism glossary also provides a variety of definitions related to race, racism, and anti-racism. 3 videos7 readings1 assignment1 discussion prompt Now that you've learned to define whiteness and other terms related to race, racism, and anti-racism, this week focuses on identifying the impact of race, racism, and anti-racism. The first article contextualizes our current moment of racial crisis, along with identifying differences between being not-racist and anti-racist. The remaining readings and viewings provide historical context for systemic racism, especially anti-Black racism in the US. 1 video8 readings1 discussion prompt For this final week of the anti-racism course you will see how the application of these terms and concepts are tied to other overlapping oppressions and how they can be used for specific anti-racism work, such as defunding the police (and why this is not as radical as people may think it is, though in many ways to imagine an anti-racist world is a radical act) and specific actions that each of us can do to be anti-racism allies and educators. 3 videos11 readings1 peer review1 discussion prompt1 plugin
|
3 modules
|
Beginner level
| null |
https://www.coursera.org/learn/antiracism-1
|
95%
|
948 |
JavaScript Basics
|
65,303
|
4.7
| 897 |
William Mead
|
University of California, Davis
|
[]
|
This course introduces the programming language JavaScript and shows the websites that include the type of interactions students will eventually be able to develop. Learners will understand the importance of how JavaScript was developed and why such history impacts the way JavaScript is currently written and in future releases. Learners will write their first scripts, have their HTML and CSS skills assessed, create variables and arrays and assign values to them. If student’s skills are lacking, resources and recommendations are provided to improve these skills. There is ample opportunity for students to practice these first, core skills. In this module, you will be introduced to JavaScript and what it can do. You will be able to identify websites that include the types of interactions you will be able to produce at the end of the entire Specialization. You will also be able to discuss the history of JavaScript and explore why this history impacts how we write JavaScript. On the web, JavaScript is used to manipulate the HTML and CSS of a webpage, after it has loaded from the server. You will be able to assess your understanding of HTML and CSS and have the opportunity through resources and recommendations for improving your skills in this area, if necessary. You will write simple JavaScript statements in the web browser console and be able to create variables and arrays. You will be able to assign values to these variables and arrays and be able to read values from them. 14 videos3 readings2 assignments2 discussion prompts In this module, you will be able to download, install and use of a code editor as a tool for writing code, and properly save and manage their files. You will be introduced to the selection control structure. This basic control structure allows programs to follow a path based on conditions, and is one of the three major logic and flow control structures found in any modern programming language. You will be able to identify, write, and trouble shoot scripts using this basic control structure. You will be able to correctly identify loop structures and practice using some of the syntax available in JavaScript to create loops. You will then be able to put all three logical flow control structures (sequence, selection, and loop) together to create basic JavaScript programs that can be tested. Finally you will be able to combine sets of program instructions into named functions and create custom functions that can be called to complete the instructions they contain. 25 videos5 readings1 assignment1 discussion prompt In this module, you will be introduced to the methods built into JavaScript for accessing and manipulating DOM elements in the web browser. You will be able to capture user events with JavaScript and use those events to trigger changes to the DOM using the document methods and element properties. You will be able to identify how scope works in JavaScript and be introduced to best practices for working with variables in JavaScript so that scope does not become a problem. You will be able to practice all the skills and techniques learned so far in the course by putting together a simple slideshow on a web page. 36 videos7 readings1 assignment3 discussion prompts In this module, you will be able to apply and practice the skills and techniques you have learned in the course by building a basic and a more advanced distance converter. You will be able to further apply and practice to extend your skills and techniques by building a simple vacation destination list application. 26 videos4 readings1 assignment6 discussion prompts
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/javascript-basics
|
96%
|
949 |
Microsoft Azure Cosmos DB
|
8,618
|
4.4
| 90 |
Microsoft
|
Microsoft
|
['Microsoft Azure', 'Relational Data', 'Data Management', 'Non-relational Data']
|
In this course, you will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build your foundational knowledge of cloud data services within Microsoft Azure. You will explore non-relational data offerings, provisioning and deploying non-relational databases, and non-relational data stores with Microsoft Azure. This is the third course in a program of five courses to help prepare you to take the Exam DP-900: Microsoft Azure Data Fundamentals, so that you can demonstrate that you have a foundational knowledge of the core database concepts in a cloud environment.
This course is ideal for IT professionals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure with a view to taking up roles as Data Engineers and Database Administrators. It is also suitable for working database professionals looking for additional skills or credentials to showcase expertise in a cloud environment and IT professionals looking to specialize in the specific area of Azure data.
To be successful in this course, you need to have basic computer literacy and proficiency in the English language. Successful Azure Data Fundamentals students start with some basic awareness of computing and Internet concepts, and an interest in extracting insights from data. It is an advantage to have experience using a web browser, familiarity with basic data-related concepts, such as working with tables of data in a spreadsheet, and visualizing data using charts. In this module, you will learn about Azure Table Storage, Azure Blob Storage, Azure File Storage, and Azure Cosmos DB, and explore situations for using them. 7 videos6 readings2 quizzes3 assignments1 discussion prompt in this module, you will learn how to provision and configure Azure Cosmos DB, Azure Data Lake , Azure Blob Storage, and Azure File Storage. 9 videos2 readings2 quizzes1 assignment2 plugins In this module, you will learn how to upload and retrieve data held in Azure Cosmos DB, Azure Blob storage, and Azure File storage. 6 videos3 readings2 quizzes1 assignment1 discussion prompt
|
3 modules
|
Beginner level
|
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/microsoft-azure-cosmos-db
| null |
950 |
UI / UX Design Specialization
|
195,199
|
4.7
| 7,147 |
Michael Worthington
|
California Institute of the Arts
|
['User Research', 'Website Wireframe', 'strategy', 'User Interface Design (UI Design)', 'User Experience (UX)', 'User Research', 'Website Wireframe', 'strategy', 'User Interface Design (UI Design)', 'User Experience (UX)']
|
The UI/UX Design Specialization brings a design-centric approach to user interface and user experience design, and offers practical, skill-based instruction centered around a visual communications perspective, rather than on one focused on marketing or programming alone. In this sequence of four courses, you will summarize and demonstrate all stages of the UI/UX development process, from user research to defining a project’s strategy, scope, and information architecture, to developing sitemaps and wireframes. You’ll learn current best practices and conventions in UX design and apply them to create effective and compelling screen-based experiences for websites or apps. User interface and user experience design is a high-demand field, but the skills and knowledge you will learn in this Specialization are applicable to a wide variety of careers, from marketing to web design to human-computer interaction. Learners enrolled in the UI/UX Design Specialization are eligible for an extended free trial (1 month) of a full product suite of UX tools fromOptimal WorkshopOpens in a new tab. Details are available in Course 3 of the Specialization, Web Design: Strategy and Information Architecture. Applied Learning Project In this Specialization you will participate in several short exercises—both visual and non-visual—to apply acquired knowledge, from organizing and structuring screen-based content, defining goals and strategy, to creating wireframes and visual mockups. By the end of this Specialization, you will have produced a mid-level digital prototype with simulated functionality, as well as a comprehensive plan for a complex website. This design-centric course examines the broad question of what an interface is and what role a designer plays in creating a user interface. Learning how to design and articulate meaning using color, type, and imagery is essential to making interfaces function clearly and seamlessly. Through a series of lectures and visual exercises, you will focus on the many individual elements and components that make up the skillset of an interface designer. By the end of this course, you will be able to describe the key formal elements of clear, consistent, and intuitive UI design, and apply your learned skills to the design of a static screen-based interface. This is the first course in the UI/UX Design Specialization, which brings a design-centric approach to user interface (UI) and user experience (UX) design, and offers practical, skill-based instruction centered around a visual communications perspective, rather than on one focused on marketing or programming alone.
These courses are ideal for anyone with some experience in graphic or visual design and who would like to build their skill set in UI or UX for app and web design. It would also be ideal for anyone with experience in front- or back-end web development or human-computer interaction and want to sharpen their visual design and analysis skills for UI or UX. This hands-on course examines how content is organized and structured to create an experience for a user, and what role the designer plays in creating and shaping user experience. You will be led through a condensed process that acts as a roadmap for developing robust UI/UX design: from ideation and sitemapping, to the creation of paper and digital prototypes. Building on the design skills learned in Visual Elements of User Interface Design, you will apply this methodology to produce a digital prototype for a multi-screen app of your own invention. By the end of this course, you will be able to describe and apply current best practices and conventions in UX design, and employ the fundamental principles of how UX design functions to shape an audience's experience of a given body of content.
This is the second course in the UI/UX Design Specialization, which brings a design-centric approach to user interface (UI) and user experience (UX) design, and offers practical, skill-based instruction centered around a visual communications perspective, rather than on one focused on marketing or programming alone.
These courses are ideal for anyone with some experience in graphic or visual design and who would like to build their skill set in UI or UX for app and web design. It would also be ideal for anyone with experience in front- or back-end web development or human-computer interaction and want to sharpen their visual design and analysis skills for UI or UX. This course is focused on the early user experience (UX) challenges of research, planning, setting goals, understanding the user, structuring content, and developing interactive sequences. While the concepts covered will translate to many kinds of interactive media (apps, digital kiosks, games), our primary focus will be on designing contemporary, responsive websites. In this course you will complete the first half of a large scale project—developing a comprehensive plan for a complex website—by defining the strategy and scope of the site, as well as developing its information architecture and overall structure. Along the way we will also discuss: - Different job descriptions in the web design industry and where UX and UI skills fall within this spectrum
- The difference between native apps and websites
- The difference of agile vs. waterfall approaches
- User personas and site personas
- User testing
The work and knowledge in this course continues in the last course in the UI/UX Design Specialization, Web Design: Wireframes to Prototypes, where you will tackle—finally—wireframes, visual mockups, and clickable prototypes.
This is the third course in the UI/UX Design Specialization, which brings a design-centric approach to user interface (UI) and user experience (UX) design, and offers practical, skill-based instruction centered around a visual communications perspective, rather than on one focused on marketing or programming alone.
These courses are ideal for anyone with some experience in graphic or visual design and who would like to build their skill set in UI or UX for app and web design. It would also be ideal for anyone with experience in front- or back-end web development or human-computer interaction and want to sharpen their visual design and analysis skills for UI or UX. This course is focused on the application of the early UX research to actual user interfaces: the creation of wireframes, high-fidelity mockups, and clickable prototypes. Along the way we will also discuss: - Responsive web design and mobile web challenges
- Mobile-first approach
- Web typography
- The relationship between design and programming and whether it is important to know how to code
- The different web technologies that make the web work, such as HTML, CSS, JavaScript, server-side coding, and databases.
This course is the continuation of the course Web Design: Strategy and Information Architecture, in which students completed the first half of a large scale project—developing a comprehensive plan for a complex website. If you are intending to complete the assignments in this course to earn a certificate you must complete the Strategy and Information Architecture course first so you have the materials and data needed to begin creating wireframes and mockups in this course.
This is the fourth and last course in the UI/UX Design Specialization, which brings a design-centric approach to user interface (UI) and user experience (UX) design, and offers practical, skill-based instruction centered around a visual communications perspective, rather than on one focused on marketing or programming alone.
These courses are ideal for anyone with some experience in graphic or visual design and who would like to build their skill set in UI or UX for app and web design. It would also be ideal for anyone with experience in front- or back-end web development or human-computer interaction and want to sharpen their visual design and analysis skills for UI or UX.
|
4 course series
|
Beginner level
|
2 months (at 10 hours a week)
|
https://www.coursera.org/specializations/ui-ux-design
| null |
951 |
Music's Big Bang: The Genesis of Rock 'n' Roll
|
8,052
|
4.7
| 146 |
Professor David Carlson
|
University of Florida
|
[]
|
Explores the factors — musical and cultural — that led to the birth of American rock 'n' roll music in the early 1950s. Covers in detail the genres, styles and people that converged to create this new music. Some basic tenets of rock 'n' roll 5 videos1 assignment1 discussion prompt There were many, many genres, styles and sub styles of American pop 11 videos1 assignment The Mississippi Delta, an area surrounding the Mississippi River, becomes the cradle of the blues 5 videos1 assignment The legend of Robert Johnson and his visit to "the crossroads" 9 videos1 assignment New Orleans is the city of jazz 5 videos1 assignment Chicago is where the blues went electric 5 videos1 assignment The delivery room of rock 'n' roll 6 videos1 assignment
|
7 modules
|
Beginner level
|
9 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/rock-and-roll-music
| null |
952 |
Geospatial Information Technology Essentials
|
Enrollment number not found
|
Rating not found
| null |
Subject Matter Expert
|
L&T EduTech
|
['Proficiency in GIS data conversion and georeferencing', 'Fundamental understanding of GIS and geospatial thinking']
|
The "Geospatial Information Technology Essentials" course offers a multi-disciplinary approach, integrating key aspects of both Geospatial and Information Technology. Organized into seven comprehensive modules, it provides a thorough learning experience. Module One introduces the fundamentals of Geographic Information Systems (GIS), covering its applications, hardware requirements, data models, and attribute data types. Module Two delves deeper into GIS concepts, focusing on mapping essentials, data conversion techniques, and georeferencing. In Module Three, learners explore GIS database management, including basics of databases, RDBMS, SQL, and advanced geodatabase management. Module Four covers spatial analysis using GIS, with practical demonstrations of techniques like catchment area delineation, overlay analysis, and viewshed analysis. Module Five provides insights into geospatial IT, including enterprise GIS, web and mobile GIS technologies, and practical case studies. In Module Six, system integrations and decision support are discussed, with a focus on command and control center case studies, decision support systems, and open-source GIS projects. Module Seven introduces future trends in geospatial technologies, highlighting advancements in survey and mapping technologies, spatial analytics, and geointelligence. Join us on this journey into Geospatial Information Technology and equip yourself with the essential skills and knowledge to excel in this dynamic field! Target Learners:
• Undergraduate students of Civil Engineering
• Post-Graduate Students in Geoinformatics/ Remote Sensing/ Geospatial Engineering.
• Practicing Engineers involved in geospatial applications in construction.
• Faculties in Civil, Geospatial and Environmental Studies.
• Professionals in GIS and Remote Sensing fields
• Engineers and project managers involved in spatial data analysis
Prerequisites:
• Basic understanding of GIS principles and spatial data
• Familiarity with computer operations and software usage
• Software: ArcGIS This module introduces the fundamentals of Geographic Information Systems (GIS), covering its basic concepts and applications. Learners will explore GIS in action, the hardware used for GIS implementations, and different GIS data models. The module also includes discussions on digital elevation models (DEM), Triangular Irregular Networks (TIN), attribute data types, and their relevance in GIS applications. 8 videos3 readings1 assignment1 discussion prompt This module focuses on mapping essentials and practical GIS data conversion techniques. Learners will understand the components and types of maps, and gain hands-on experience in converting data from various formats like Excel and CAD to GIS-compatible formats. The module also covers georeferencing techniques for integrating raster data into GIS applications. 7 videos1 assignment1 discussion prompt This module provides a comprehensive overview of GIS database management principles. Learners will explore foundational concepts such as database basics, relational database management systems (RDBMS), and Structured Query Language (SQL) as applied to GIS databases. Advanced topics include the creation and configuration of geodatabases, enterprise geodatabases, and their management in GIS environments. 6 videos1 assignment1 discussion prompt This module explores advanced spatial analysis techniques using Geographic Information Systems (GIS). Learners will delve into methods such as catchment area delineation, overlay analysis, cluster analysis, hotspot analysis, and viewshed analysis. Each technique is demonstrated through practical examples to illustrate their application in spatial data analysis. 6 videos1 assignment1 discussion prompt This module provides an introduction to Geospatial Information Technology (Geospatial IT) and its components. Learners will explore enterprise GIS systems, web GIS technologies including essentials and application overview, mobile GIS technologies along with their technical stack, and various case studies showcasing the practical applications of Geospatial IT in scenarios like emergency response. 9 videos1 assignment1 discussion prompt This module focuses on system integrations and decision support in Geospatial IT. Learners will explore methods for integrating devices into GIS systems, case studies on command & control centers, and the implementation of decision support systems. The module also covers progress and spatial dashboards, highlighting their role in monitoring and reporting spatial data. Additionally, the module introduces open-source GIS technologies and guides learners through creating their own web applications using open-source tools. 9 videos1 assignment1 discussion prompt This module explores the evolving landscape of geospatial technologies and their future trends. Learners will examine the benefits realized from geospatial technologies through case studies, advancements in modern surveying and mapping technologies, and emerging trends in spatial analytics and geo-intelligence. The module concludes by discussing future directions and the potential impact of geospatial technologies on various sectors. 9 videos1 assignment1 discussion prompt
|
7 modules
|
Intermediate level
|
13 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/geospatial-information-technology-essentials
| null |
953 |
Project Management Communication, Stakeholders & Leadership
|
10,865
|
4.6
| 103 |
Daniel C. Yeomans
|
SkillUp EdTech
|
['Project Management', 'Communication', 'Leadership', 'Stakeholder Management']
|
Project management is a highly valued skill that provides a structured approach to managing projects. Communication, stakeholder management, leadership skills are core to any project manager's success. This course is intended for anyone interested in project management, be it a beginner or an experienced professional looking to switch or advance their career in project management.
In this course, you will learn how to lead, communicate, and manage stakeholders as a project manager. This course will teach you how to cultivate a healthy project environment and review the benefits of empowering team members. You will learn different ways of communicating with team members across different types of stakeholders using appropriate communication mediums and channels. You will explore the leadership skills used to improve stakeholder engagement and facilitate successful projects from their inception through closing.
Throughout this course, you will work with numerous hands-on labs and real-world examples to develop your communication, leadership, and stakeholder management skills.
This course is part of a series of courses that will help you prepare for certifications offered by the Project Management Institute (PMI) including Certified Associate of Project Management (PMI-CAPM) and Project Management Professional (PMI-PMP).
RECOMMENDED: It is good for everyone gearing toward a career in Project Management to have basic to intermediate skills in an Office Productivity Suite, such as Microsoft Office 365. We highly recommend enrolling in the SkillUp EdTech Office Productivity Software Specialization, which covers Word Processing, Spreadsheets, PowerPoint, Messaging, and Email. Welcome to Module 1, where we will explore various methods to cultivate a positive and productive atmosphere for team members. A key aspect of a healthy environment is to “put people first.” We will examine how empowering team members can improve project outcomes. Additionally, we will dive into the importance of project objectives and how objective awareness can prevent scope creep. We will also explore the responsibility of a project manager in developing and communicating project objectives to the team and stakeholders. Finally, we will introduce the concept of servant leadership, its benefits, and tips to become a good servant leader. 5 videos3 assignments2 discussion prompts5 plugins Welcome to Module 2, where we will explore the definition of numerous communications best practices and take a deep dive into the process of managing end-to-end project communications. We will look at different communication mediums and understand the concepts of the gulf of execution and the gulf of evaluation to identify communication gaps. We will touch on the failing fast concept and how the approach can help turn a failing project into a success. Finally, we will review the different roles that engage in a project and how the RACI matrix can be used to assign responsibilities. 12 videos5 assignments3 discussion prompts6 plugins Welcome to Module 3, where we will introduce two common methods used to establish and effectively communicate an acceptable schedule baseline. The methods include critical chain and critical path method. We will also explain and illustrate a communications management plan.
In addition, we will revisit the need to plan virtual communications effectively. We will discuss status reporting essentials and share how various communication styles can impact the quality of communications. 9 videos3 assignments1 discussion prompt9 plugins Welcome to Module 4, where we will introduce some critical leadership skills, attributes, and styles. We will also cover the key differences between a manager and a leader. We will look at how to be effective as a leader in different situations. In addition, we will review the importance of knowledge sharing and understand why intuitive decision-making is an important skill for a leader. 9 videos5 assignments3 discussion prompts7 plugins Welcome to Module 5, where we will explore effective resource management practices, including the resource breakdown structure (RBS) tool. You will learn the techniques to plan for and acquire resources, the challenges you may face, and strategies to overcome the challenges. You will also explore the principles and benefits of effective negotiation. 6 videos3 assignments2 discussion prompts5 plugins In this module, you will complete a final exam that tests your knowledge of the course’s content. The exam will include questions on topics including but not limited to effective communication, managing stakeholders, and effective leadership. You will also have the opportunity to demonstrate your skills in project management communications, stakeholder management, and leadership skills through a peer-graded final project. 1 assignment1 peer review9 plugins
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/project-management-communication-stakeholders-and-leadership
|
97%
|
954 |
Technical Managerial Written Skills
|
1,676
|
Rating not found
| null |
Daniel Moorer
|
University of Colorado Boulder
|
['Business Writing', 'Influence', 'Targeting your audience', 'Brevity', 'Clarity']
|
Writing effective documents to influence teams and decision-makers is one of the essential elements of successful management. Additionally, in all of its forms, writing remains one of the primary vehicles by which a leader exercises leadership. Just like the other forms of communication, it must be coherent, complete, make a clear argument, and include appropriate decorum. This course focuses on these attributes as applied in all forms of modern written communication. This course can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder. The best trait when working to achieve effective and professional writing is humility. Although all of us consider ourselves above-average writers, the fact is that there are only a few who rise above the rest with "perfect" documents that achieve "flow", and exercise exceptional word choice, correct paragraph sentence and paragraph structure, and perfect grammar, punctuation, capitalization, and hyphenation. These, then are the attributes and standards we hope to achieve starting with this first module. Our goal is that each of us rise above our current level of writing expertise. 4 videos7 readings1 peer review8 discussion prompts The most fundamental business writing exercise is exemplified by the "Letter To the External Stakeholder". In addition, there are the larger questions that are addressed here. These include the viability of letter writing as a business practice; the fundamentals including formatting, grammar, punctuation, paragraph formation; the importance of word choice; and the very important practice of proofreading. All of this is an important first step for improving one's writing skills. 4 videos4 readings1 quiz1 peer review8 discussion prompts A common element of writing in business and industry is the Research Proposal. The "proposal" is a common tool in business and industry used to compete for future business. Proposals are not just statements of what you or your business are capable of doing; there will be many bidders who will make the same statement. Instead, your proposal must CONVINCE the customer that you are the best choice of vendor for their upcoming work. In the effort to convince them, you must write to the customer's primary concerns, create a clear mental picture for the reader of your proposal, be brief and concise, and be perfect in format and all of the other writing fundamentals. Therefore, I offer this module as support for this most-common form of business writing. 4 videos4 readings1 quiz1 peer review7 discussion prompts The most useful written tool for the aspiring manager-leader is the Executive Summary. Although it is usually found as the first element of a proposal, it can also be used to summarize facts and recommendations for your supervisor. So, in this module, we'll learn about the value of the one-page executive summary and how to apply the skills we learned in weeks 2 and 3 to make our executive summary even better. 4 videos4 readings1 quiz1 peer review8 discussion prompts
|
4 modules
|
Beginner level
|
15 hours to complete (3 weeks at 5 hours a week)
|
https://www.coursera.org/learn/technical-managerial-written-skills
| null |
955 |
Cybersecurity: Protecting your Information at Home
|
Enrollment number not found
|
Rating not found
| null |
Herbert J. Mattord, Ph.D., CISM, CISSP, CDP
|
Kennesaw State University
|
['Desktop Computing', 'Smartphone Operation']
|
Cybersecurity is essential for everyone who uses information or communications technologies. Whether it is a computer, tablet, or smartphone, if it is connected to a network, learn about the technical infrastructure that connects it to the Internet. The objectives of this course are:
-Understand the elements of home computing.
-Recognize the steps needed to secure the home computing environment.
-Explain how to secure the use of email.
-Recognize and protect against Web browsing threats. This is the second course in the Cybersecurity Awareness for Everyone specialization. 1 video Securing Your Information 7 videos6 assignments 6 videos5 assignments Securing Email 6 videos5 assignments Securing Web Browsing 4 videos4 assignments 1 video1 assignment
|
6 modules
|
Beginner level
|
6 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/csafe-protecting-your-information-at-home
| null |
956 |
Fundamental Skills in Engineering Design
|
7,816
|
4.7
| 123 |
AMMAR ALSALKA
|
University of Leeds
|
['Problem Solving', 'Requirements Elicitation', 'Engineering Design']
|
The engineering design process allows engineers to execute both small- and large-scale projects by applying scientific knowledge to the solution of technical problems. Understand the key principles and techniques of engineering design that will help you to develop in this field. In this course, you will explore the fundamental aspects of engineering design, including requirement gathering, problem-solving and project management. You will actively engage in real-world design scenarios, honing your problem-solving abilities and gaining hands-on experience.
By the end of the course, you will be able to confidently gather requirements and solve complex problems, ensuring your designs contribute positively to society.
Enrol now to learn key skills that may help you to start your professional journey in engineering design. Welcome to Fundamental Skills in Engineering Design! The first week of the course will give you a basic understanding of what we mean by 'engineering design', as well as an exploration of the product life cycle. You will learn about the the engineering design process this week too, which is what designers do in order to come up with a new product. This will give you a solid foundation on which to build on in Week 2. Let's get started! 12 videos15 readings3 assignments3 discussion prompts Welcome to Week 2! This week you will examine some of the soft skills that you will need for a role in engineering design before moving on to look at a case study that will give you the opportunity to think about and practice some of the elements of conceptual design. 1 video13 readings1 assignment2 discussion prompts
|
2 modules
|
Beginner level
|
6 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/fundamental-skills-in-engineering-design
| null |
957 |
Health Care Innovation
|
10,952
|
4.6
| 288 |
Christian Terwiesch
|
University of Pennsylvania
|
[]
|
In this course, you’ll learn the foundational economic theories behind health care innovation and how to optimize your own health care practice or organization. Designed to help you gain a practical understanding of the theoretical frameworks of behavioral economics and operations management in the health care setting, this course will help you apply these frameworks to assess health care practices and apply innovation while managing risk. You’ll also explore the best practices for evaluating one’s innovative practices, using real-life examples of success to see the concepts in action. By the end of this course, you’ll have honed your skills in optimizing health care operations, and be able to develop the right set of evaluations and questions to achieve best innovative practices within your organization. This module was designed to give you a foundational knowledge of health care operations and methods of optimization. You’ll examine the provider-patient relationship and learn how a provider can improve performance measures for the patient by analyzing the different types of performance metrics such as patient-centric, operations, and financial measures. Through discussing the different types of inefficiencies such as waste, variability, and inflexibility, you’ll be able to optimize performance and service. You’ll also learn how to gauge patient flow by flow rate, flow time, and inventory, and be able to map processes using a flow diagram and a Gantt chart. By the end of this module, you’ll be better able to calculate the financial viability of a health care provider using Key Performance Indicators (KPI) and create a framework to assess and optimize performance. 9 videos1 reading1 assignment In this module, you’ll see how techniques in innovation that originally developed outside of health care can be deployed successfully in health care systems and organizations. Using your understanding of optimizing health care operations, you’ll be able to apply innovative techniques to a more traditional ecosystem of health care. You’ll learn how innovative researchers and clinicians changed some of the more grounded approaches to health care. Through analyzing the scientific method, you’ll be able to craft a hypothesis statement of your innovative idea and identify key assumptions in your statement to test first. By the end of this module, you’ll be able to successfully assess the value and plausibility of the hypothesis of your innovation, and effectively utilize successful instances of innovation to your health care practice. 5 videos1 reading1 assignment In this module, you’ll examine the practice of evaluation and how it is applied to health policy and programs. You’ll gain a better understanding of the need for evaluations in an ever-changing health care environment, and the importance of control groups to combat selection bias that may skew the findings of an evaluation. You’ll explore different methods to conducting an evaluation, the types of questions an evaluation aims to answer, and the difference between effectiveness and efficacy. By the end of this module, you’ll understand the theoretical framework behind an evaluation and be able to employ an evaluation to better analyze the effectiveness of your health care organization. 6 videos1 reading1 assignment This module was designed to highlight the importance of behavioral economics in health care practice and how to utilize behavioral economic theory to optimize the operations of your health care organization. You’ll explore Expected Utility Theory and the different types of Prospect theory such as Reference Dependence, Diminished Sensitivity, and Loss Aversion in the context of health care. By studying real-life examples of Default Bias and Increased Cost Sharing case studies, you’ll establish a framework for health care interventions that will be effective and successful after implementation. By the end of this module, you’ll be better able to determine the theoretical basis for certain health care practices such as nudge units and whether such practices would benefit your organization. 7 videos1 reading1 assignment
|
4 modules
| null |
6 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/wo-pmo-healthcareinnovation
| null |
958 |
Tencent Cloud Practitioner
|
2,074
|
4.7
| 46 |
Anthony Siu
|
Tencent Cloud
|
['Tencent Cloud Products', 'Cloud Computing', 'basic cloud knowledge', 'Tencent Cloud']
|
This course is primarily aimed at cloud professionals who are interested in learning about Tencent Cloud's products and services. It equips learners with a foundational knowledge in cloud computing and prepares them to take the Tencent Cloud Practitioner examination. After completing this course, learners will be able to explain the different features, advantages, uses cases, and billing methods of several core Tencent Cloud products. 5 videos1 assignment 3 videos1 assignment 4 videos1 assignment 5 videos1 assignment 4 videos1 assignment 5 videos1 assignment 5 videos1 assignment 1 reading1 assignment
|
8 modules
|
Beginner level
|
8 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/tencent-cloud-practitioner
| null |
959 |
Big Data Analysis with Scala and Spark (Scala 2 version)
|
2,227
|
Rating not found
| null |
Prof. Heather Miller
|
École Polytechnique Fédérale de Lausanne
|
['Scala Programming', 'Big Data', 'SQL', 'Apache Spark']
|
Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We'll cover Spark's programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections. Through hands-on examples in Spark and Scala, we'll learn when important issues related to distribution like latency and network communication should be considered and how they can be addressed effectively for improved performance. Learning Outcomes. By the end of this course you will be able to:
- read data from persistent storage and load it into Apache Spark,
- manipulate data with Spark and Scala,
- express algorithms for data analysis in a functional style,
- recognize how to avoid shuffles and recomputation in Spark,
Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Parallel Programming: https://www.coursera.org/learn/parprog1.
Note that this version of the course uses Scala 2.13. You can find a more recent version of the course that uses Scala 3 here: https://www.coursera.org/learn/scala-spark-big-data Get up and running with Scala on your computer. Complete an example assignment to familiarize yourself with our unique way of submitting assignments. In this week, we'll bridge the gap between data parallelism in the shared memory scenario (learned in the Parallel Programming course, prerequisite) and the distributed scenario. We'll look at important concerns that arise in distributed systems, like latency and failure. We'll go on to cover the basics of Spark, a functionally-oriented framework for big data processing in Scala. We'll end the first week by exercising what we learned about Spark by immediately getting our hands dirty analyzing a real-world data set. 7 videos6 readings3 programming assignments This week, we'll look at a special kind of RDD called pair RDDs. With this specialized kind of RDD in hand, we'll cover essential operations on large data sets, such as reductions and joins. 4 videos2 programming assignments This week we'll look at some of the performance implications of using operations like joins. Is it possible to get the same result without having to pay for the overhead of moving data over the network? We'll answer this question by delving into how we can partition our data to achieve better data locality, in turn optimizing some of our Spark jobs. 4 videos With our newfound understanding of the cost of data movement in a Spark job, and some experience optimizing jobs for data locality last week, this week we'll focus on how we can more easily achieve similar optimizations. Can structured data help us? We'll look at Spark SQL and its powerful optimizer which uses structure to apply impressive optimizations. We'll move on to cover DataFrames and Datasets, which give us a way to mix RDDs with the powerful automatic optimizations behind Spark SQL. 5 videos2 programming assignments
|
4 modules
|
Intermediate level
|
27 hours to complete (3 weeks at 9 hours a week)
|
https://www.coursera.org/learn/scala2-spark-big-data
| null |
960 |
Black Performance as Social Protest
|
Enrollment number not found
|
Rating not found
| null |
Scott Piper
|
University of Michigan
|
['Equity', 'social activism', 'Social Justice']
|
Black performance and social activism have been a model for protest globally. It has enriched and activated cries for justice in multiple contexts. This course will help you expand your understanding of Black performance as social protest and its active effects on performance and protest today. The arts are a potent way of responding to issues of injustice. From slavery and lynching to incarceration and disenfranchisement, Black performance has resisted oppression across several historical frames. On this course, you’ll read, watch, and listen to performances that illustrate various forms of artistic protest from the African Diaspora. You’ll cover chants of the enslaved and dances of heritage, before moving on to look at early 20th century migrations and United States protests.
You’ll identify ways in which patterns of resistance from the past contribute to ongoing social justice movements, such as Black Lives Matter. After investigating the history of Black performance as social protest, you’ll produce a reflective manifesto for achieving racial equity through performance. This week we will be examining Black performance and representation in the age of slavery and beyond. We will begin to assess how protest developed and solidified in Black performance in the United States. 2 videos15 readings1 app item6 discussion prompts This week we will be examining how Black performance developed in response to the socio-political events of the early 20th century including migrations and protests in the United States. We will explore patterns of resistance within Black performance of this time. 3 videos9 readings3 app items6 discussion prompts This week we will be exploring Black performance of the Civil Rights Era and beyond including how it both defined and enlivened the global movement for Civil Rights and Black Nationalism. 2 videos8 readings1 app item7 discussion prompts This week you will expand on the concepts of the past and explore how they affect us in the present. You will also look at modern protest movements and explore how the use of performance manifests in the modern age. 1 video11 readings2 app items7 discussion prompts The final week of the course will culminate in a self-directed manifesto. To prepare for this we will explore other manifestos that have come out of the performance world. 2 videos11 readings2 app items6 discussion prompts
|
5 modules
|
Beginner level
|
23 hours to complete (3 weeks at 7 hours a week)
|
https://www.coursera.org/learn/black-performance-as-social-protest
| null |
961 |
Data Analysis with R
|
27,633
|
4.7
| 311 |
Tiffany Zhu
|
IBM
|
['Data Science', 'Data Analysis', 'Statistical Analysis', 'Data Visualization', 'R Programming']
|
The R programming language is purpose-built for data analysis. R is the key that opens the door between the problems that you want to solve with data and the answers you need to meet your objectives. This course starts with a question and then walks you through the process of answering it through data. You will first learn important techniques for preparing (or wrangling) your data for analysis. You will then learn how to gain a better understanding of your data through exploratory data analysis, helping you to summarize your data and identify relevant relationships between variables that can lead to insights. Once your data is ready to analyze, you will learn how to develop your model and evaluate and tune its performance. By following this process, you can be sure that your data analysis performs to the standards that you have set, and you can have confidence in the results. You will build hands-on experience by playing the role of a data analyst who is analyzing airline departure and arrival data to predict flight delays. Using an Airline Reporting Carrier On-Time Performance Dataset, you will practice reading data files, preprocessing data, creating models, improving models, and evaluating them to ultimately choose the best model.
Watch the videos, work through the labs, and add to your portfolio. Good luck!
Note: The pre-requisite for this course is basic R programming skills. For example, ensure that you have completed a course like Introduction to R Programming for Data Science from IBM. All data analysis starts with a problem that you need to solve and understanding your data and the types of questions you can answer about it are key aspects of this. The R programming language provides you with all the tools you need to conduct powerful data analysis, providing the conduit between your data and the real-world problems you want to solve.
In this module, you’ll review a type of problem that you can solve in R and the underlying data that forms the basis for your analysis. You’ll also learn about the R packages for data analysis, which provide a powerful set of tools that you’re likely to use in everyday data analyses. Finally, you’ll see how to import data and gain basic insights from the dataset. 6 videos1 reading2 assignments1 app item1 plugin Data wrangling, or data pre-processing, is an essential first step to achieving accurate and complete analysis of your data. This process transforms your raw data into a format that can be easily categorized or mapped to other data, creating predictable relationships between them, and making it easier to build the models you need to answer questions about your data.
This module provides an introduction to data pre-processing in R and then provides you with the tools you need to identify and handle missing values in your dataset, transform data formats to align them with other data you may want to compare them to, normalize your data, create categories of information through data binning, and convert categorical variables into quantitative values that can then be used in numeric-based analyses. 6 videos1 reading2 assignments1 app item1 plugin Exploratory data analysis, or EDA, is an approach to analyzing data that summarizes its main characteristics and helps you gain a better understanding of the dataset, uncover relationships between different variables, and extract important variables for the problem you are trying to solve.
The main question you are trying to answer in this module is: "What causes flight delays?" In this module, you’ll learn some useful exploratory data analysis techniques that will help answer this question. 5 videos1 reading2 assignments1 app item1 plugin You have identified the problem that you’re trying to solve and have pre-processed the dataset you’ll use in your analysis, and you have conducted some exploratory data analysis to answer some of your initial questions. Now, it’s time to develop your model and assess the strength of your assumptions.
In this module, you will examine model development by trying to predict the arrival delay of a flight using the Airline dataset. You’ll learn regression techniques for determining the correlation between variables in your dataset, and evaluate the result both visually and through the calculation of metrics. 7 videos1 reading2 assignments1 app item1 plugin You have a firm understanding of your data and have pre-processed it to ensure the best possible outcomes. And you have conducted exploratory data analysis and developed your model. Everything looks good so far, but how can you be certain your model works in the real world and performs optimally?
In this module, you’ll learn how to use the tidymodels framework to evaluate your model. Tidymodels is a collection of packages for modeling and machine learning using tidyverse principles. Using these packages, you’ll learn how to cross-validate your models, identify potential problems, like overfitting and underfitting, and handle overfitting problems using a technique called regularization. You’ll also learn how to tune your models using grid search. 4 videos1 reading2 assignments1 app item1 plugin 4 readings1 assignment1 peer review2 app items3 plugins
|
6 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/data-analysis-with-r
|
95%
|
962 |
Visual Perception and the Brain
|
35,007
|
4.6
| 265 |
Dale Purves
|
Duke University
|
[]
|
Learners will be introduced to the problems that vision faces, using perception as a guide. The course will consider how what we see is generated by the visual system, what the central problem for vision is, and what visual perception indicates about how the brain works. The evidence will be drawn from neuroscience, psychology, the history of vision science and what philosophy has contributed. Although the discussions will be informed by visual system anatomy and physiology, the focus is on perception. We see the physical world in a strange way, and goal is to understand why. 20 videos2 readings2 assignments 17 videos2 assignments 19 videos2 assignments 9 videos1 assignment 11 videos2 assignments1 peer review
|
5 modules
| null |
14 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/visual-perception
|
96%
|
963 |
Electric Power Systems
|
115,178
|
4.7
| 7,462 |
Ilya Grinberg
|
University at Buffalo
|
[]
|
This course familiarizes you with standards and policies of the electric utility industry, and provides you with basic vocabulary used in the business. It introduces the electric power system, from generation of the electricity all the way to the wall plug. You will learn about the segments of the system, and common components like power cables and transformers. This course is for individuals considering a career in the energy field (who have a high school diploma, at minimum, and basic knowledge of mathematics), and existing energy sector employees with less than three years of experience who have not completed similar training and would benefit from a course of foundational industry concepts.
The course is a combination of online lectures, videos, readings and discussions.
This is the first course in the Energy Production, Distribution & Safety specialization that explores various facets of the power sector, and features a culminating project involving creation of a roadmap to achieve a self-established, energy-related professional goal. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=2Yh9qIYiUDk. Electricity is a term that covers all the phenomena caused either by static electric charge or by the movement of charge (current) and the electrical and magnetic fields associated with that.
This module looks at: Nature and Effects of Electricity; Basic Electrical Properties and Simple Circuits. 6 videos2 readings6 assignments Electrical energy is transmitted and distributed via overhead lines and underground cables operating at different voltage levels. It is necessary to mesh networks to ensure dependable supply for consumers even if individual transmission paths fail.
This module focuses on: Substations & Transformers; Generation; Transmission & Subtransmission and Distribution. 4 videos1 reading5 assignments Circuit breakers are complicated electromechanical devices and must be serviced regularly. So that work on them can be perform safely, switches are installed before and after them. 3 videos1 reading4 assignments Our nation’s electric power infrastructure that has served us so well for so long – also known as “the grid” – is rapidly running up against its limitations.
This module looks at Smart Grid Risks; Smart Grid, Utilities & Customers; Smart Grid & the Environment and Renewable Energy. 4 videos4 readings5 assignments
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/electric-power-systems
|
95%
|
964 |
Relativism
|
8,814
|
4.3
| 39 |
Annalisa Coliva
|
University of California, Irvine
|
[]
|
Relativism is an ancient philosophical doctrine which has recurred time and again in the history of philosophy. It has also transcended the boundaries of that discipline, for it has shaped much of the methodology in anthropology and sociology, as well as in critical theory and literary studies. While often advocated for its supposed tolerance of differences, relativism has profound consequences for how we think of reality, for the possibility of knowledge, both in the factual and in the moral domain, and may engender the practice of double standard. If a wind is hot for me and cold for you and none of us is at fault, does this mean that reality is always perspectival, or that it admits of contradictory descriptions? If a belief turns out to be justified when evaluated within a certain epistemic system (such as religion, for instance), while it turns out to be unjustified if assessed from within a different one (science, say), does relativism undermine the very possibility of knowledge? If an action can be morally permissible within an ethical system and not so within a different one, does that challenge the idea that there are moral truths and moral progress? These are some of the questions we will engage in during the course, while considering examples taken from the history of science, such as the Bellarmine-Galileo dispute, and from everyday life.
This course is aimed at anyone who is interested in learning more about philosophy, along with those who are looking for strategies to combat extremism in their communities. Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life.
In this course, learners will:
Explore the concept of Relativism
Discuss the role of Relativism in contemporary society
Identify common responses to Relativism
Compare/Contrast various forms of Relativism
Recognize how epistemic relativism can be used to explain important events in the history of science and crucial discoveries in anthropology
Create a presentation with your personal perspective on one of the forms of relativism Welcome to Module 1: Introduction to Relativism. In this module, we will explore how current issues in public debate (climate change denial, fake news, vaccine skepticism, religious and political extremism) trade on relativism, and how relativism may be thought of as being a source of good by promoting pluralism and tolerance. We will begin by defining Relativism, and review the various forms, including faultless disagreement, relativism of difference, and local vs. global Relativism. 2 videos1 reading1 assignment1 discussion prompt Welcome to Module 2: Alethic Relativism. This week we will explore the structure of alethic relativism in Protagoras’ philosophy, examine the structure of contemporary alethic relativism, and identify the main objections to both forms of alethic relativism. 1 video1 reading1 assignment1 discussion prompt Welcome to Module 3: Epistemic Relativism. In this module we will explore the structure of epistemic relativism and identify how epistemic relativism can be used to explain important events in the history of science and crucial discoveries in anthropology. We will also review the main objections to epistemic relativism and examine how the data provided by the history of science and anthropology could be understood without appealing to epistemic relativism. 1 video1 reading1 assignment1 discussion prompt Welcome to Module 4: Moral Relativism. In this module we will explore the structure and framework of ethical relativism and review alethic relativism and relativism of distance as applied to ethics. We will identify the main objections to these forms of ethical relativism and recognize the difficulty of formulating a coherent relativist proposal. Finally, course participants are asked to apply their understanding of one of the forms of relativism and create a presentation to share their personal perspective. 1 video2 readings1 assignment1 peer review1 discussion prompt
|
4 modules
|
Intermediate level
|
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/relativism
| null |
965 |
Excel Fundamentals for Data Analysis
|
175,568
|
4.8
| 3,826 |
Nicky Bull
|
Macquarie University
|
['Data Analysis', 'Microsoft Excel', 'Data Cleansing']
|
As data becomes the modern currency, so the ability to analyse the data quickly and accurately has become of paramount importance. Excel with its extraordinarily broad range of features and capabilities is one of the most widely used programs for doing this. In the first course of our Excel Skills for Data Analysis and Visualization Specialization, you will learn the fundamentals of Excel for data analysis. When you have completed the course, you will be able to use a range of Excel tools and functions to clean and prepare data for analysis; automate data analysis with the help of Named Ranges and Tables; and use logical and lookup functions to transform, link and categorise data. This course will enable you to build a strong foundation in the fundamentals, helping you to be more efficient in your day-to-day and developing the necessary skills to work with the more advanced techniques used in later courses. To make the content easy to relate to and to personalize the learning experience, we are going to follow Zara's journey through the course. Who is Zara? Well, she is no-one and everyone. You will find that Zara's trials and tribulations sound familiar, and together with Zara, you will develop your Excel skills along the way — and, importantly, have some fun doing it.
The Excel Skills for Data Analytics and Visualization courses are the sequel to one of most successful specializations on Coursera, Excel Skills for Business, which has attracted hundreds of thousands of learners and top ratings. Transform your skills, your confidence, and your opportunities by adding this new set of skills to your repertoire. 1 video3 readings1 discussion prompt By the end of this module, you will be an expert in Excel's Text functions. This module discusses ways you can extract information and manipulate data to fulfil specific business requirements. You will develop techniques for working confidently with these Excel functions and unlock the full power of Excel by manipulating and cleaning text data. This is really important because you cannot properly analyse data if it is invalid or in an unsuitable format. You will begin with the mechanics of creating a function, specifying multiple arguments, and then you will look at how to work with text in functions. You will also learn how to use multiple functions in a single formula — a technique known as nesting. The topics you will be learning this week: Functions for Combining Text; Functions for Splitting Text; Combining Text Functions; Cleaning Data & Changing Case; and Removing and replacing unwanted characters. 6 videos4 readings6 assignments By the end of this module, you will be an expert in Excel's Date functions. This module discusses ways that you can extract information and manipulate data to fulfil specific business requirements. You will also
be looking at functions for converting data types: such as text to numbers, dates to text, and then both numbers and text to dates. You will learn to solve the problem of data not being in the correct format, and you will learn how to perform arithmetic operations with dates like you would with numbers, as well as performing calculations with dates. You will also learn some really great functions specifically for solving day-to-day tricky date problems that are required in business such as the WORKDAY, EDATE and EOMONTH functions. The topics you will be learning this week: Converting Data Types; Understanding dates and basic date functions; Generating valid dates; Calculating days between two dates; and Calculating dates from a given date. 6 videos3 readings6 assignments In this module, you will learn about different types of cell referencing: relative cell referencing, absolute cell referencing, and mixed cell referencing. You will then learn about a great Excel functionality, Named Ranges — which is another way of referencing a cell or a range of cells by giving them a sensible name. You will see that named ranges make our formulas much easier to understand and you will also see how it makes them much easier to create — using tools such as Define Name and Create from Selection. You will also learn about Excel's Name Box and the Name Manager. You will learn some exciting Excel functions that allow you to aggregate and summarise data — such as SUMIFS and COUNTIFS, and much more. The topics you will be learning this week: Cell referencing and naming; Creating named ranges; Managing named ranges; Calculations with named ranges; and Automating processes with named ranges. 6 videos3 readings6 assignments In this module, you will learn that a table in Excel is more like a database of records and fields which contains a set of related information — such as a table of inventory data. You will learn how to create, format, and manage tables, and you will learn how to easily format, select, sort, and filter in a table. You will also learn about the Total Row where you can just pick from a set of automated summarisation functions. You will learn about structured referencing — where you can continue to work with the data in a table, but the formulas look slightly different because tables use a different way to reference cells. You will also learn how to automatically extend tables whenever new data is added. The topics you will be learning this week: Creating, naming and removing tables; Formatting and selecting in tables; Sorting and filtering tables; Performing calculations with structured references; and Automating processes with tables. 6 videos3 readings6 assignments You will learn two great Excel skills in this week’s module — first, you will learn about conditional logic, and second, you will learn about automating lookups. The two of these tools together will push your data analytics to the next level! Excel has several logical functions and this module explores some of them, such as AND, OR, and IF. You will start by learning the concept of conditional logic, and how conditional logic works in Excel formulas. You will then learn to conduct logic tests and use conditional operations. For more complex logic tree scenarios, you will learn how to use nested IF functions to evaluate data. You will then learn about lookup functions — these are widely used in data analytics for connecting data sets as well as error checking. You will learn about one of the most widely used lookup functions in business — VLOOKUP, as well as other lookup functions such as INDEX and MATCH, as well as Excel newest lookup function — XLOOKUP. The topics you will be learning this week: Performing logical operations with IF; Applying advanced logical operations; Categorising data with VLOOKUP; Matching data with VLOOKUP and XLOOKUP; and Advanced data matching with INDEX and MATCH. 6 videos3 readings6 assignments This is the final assessment of the course and it is worth 25% of your total grade. As this is the final assessment, it requires you to demonstrate the learning objectives from each of the weeks — and thus requires you to demonstrate all the learning objectives of the entire course. 1 assignment
|
7 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/excel-data-analysis-fundamentals
|
96%
|
966 |
Chemical Hazards: Toxicology & Reactivity
|
Enrollment number not found
|
4.8
| 22 |
Jason White
|
University of California, Davis
|
[]
|
This course aims to provide process safety experience for engineers, particularly relevant to chemical engineering but applicable to any field involving process operations. This course introduces you to the important, practical, value-added skills and information that will aid your career, or preparation for a career, in chemical process engineering. These skills include improving your ability to identify and quantify toxic chemical hazards and be able to identify and mitigate scenarios where reactive chemical hazards are present. You will be able to describe the importance of pressure protection and the general process for pressure relief system design all while using lessons learned from past chemical process incidents to inform the implementation of safer solutions and work practices. After this module, you will be able to define industrial health and hygiene including important regulatory agencies. You'll be able to describe chemical hazards and the importance of understanding these hazards. You will be able to describe how chemical reactions, when not managed properly, can result in catastrophic scenarios. Finally, you will be able to use the Globally Harmonized System (GHS) for Safety Data Sheets and Labels as well as the National Fire Protection Association (NFPA) diamond. 7 videos1 reading1 assignment2 discussion prompts After this module, you will be able to define, discuss, and use exposure limits such as threshold limit value (TLV) and permissible exposure limit (PEL). You will be able to describe effects of toxicants and quantify impact of exposure using dose versus response curves. You will be able to describe control techniques to prevent exposures, as well as use lessons from past chemical process safety incidents to inform the implementation of solutions and work practices. 6 videos1 assignment2 discussion prompts After this module, you will be able to identify processes and situations where reactive chemical hazards are likely to be present. You will be able to create and use a chemical compatibility matrix. And finally, you will be able to describe how to use calorimeter data to characterize chemical reactions. 8 videos2 readings1 assignment1 discussion prompt At the end of this module, you will be able to explain the importance of pressure protection and define key terms related to pressure relief devices. You will be able to identify major classes of relief devices and be able to describe options for handling relief effluent. Finally, you'll be able to describe the general process for relief system design. 7 videos1 assignment2 discussion prompts
|
4 modules
|
Intermediate level
|
8 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/chemical-hazards-toxicology-and-reactivity
| null |
967 |
Integral Calculus through Data and Modeling Specialization
|
3,184
|
4.8
| 68 |
Joseph W. Cutrone, PhD
|
Johns Hopkins University
|
['Modeling', 'Data Analysis', 'Calculus', 'functional analysis', 'vectors', 'Modeling', 'Data Analysis', 'Calculus', 'functional analysis', 'vectors']
|
This specialization builds on topics introduced in single and multivariable differentiable calculus to develop the theory and applications of integral calculus. , The focus on the specialization is to using calculus to address questions in the natural and social sciences. Students will learn to use the techniques presented in this class to process, analyze, and interpret data, and to communicate meaningful results, using scientific computing and mathematical modeling. Topics include functions as models of data, differential and integral calculus of functions of one and several variables, differential equations, and optimization and estimation techniques. Applied Learning Project In each module, learners will be provided with solved sample problems that they can use to build their skills and confidence followed by graded quizzes to demonstrate what they've learned. Through a cumulative project, students will apply their skills to model random chance events, evaluate a policy on air pollution regulation, and use calculus to estimate surface areas of land masses. This course continues your study of calculus by introducing the notions of series, sequences, and integration. These foundational tools allow us to develop the theory and applications of the second major tool of calculus: the integral. Rather than measure rates of change, the integral provides a means for measuring the accumulation of a quantity over some interval of input values. This notion of accumulation can be applied to different quantities, including money, populations, weight, area, volume, and air pollutants. The concepts in this course apply to many other disciplines outside of traditional mathematics. Through projects, we will apply the tools of this course to analyze and model real world data, and from that analysis give critiques of policy. Following the pattern as with derivatives, several important methods for calculating accumulation are developed. Our course begins with the study of the deep and significant result of the Fundamental Theorem of Calculus, which develops the relationship between the operations of differentiation and integration. If you are interested in learning more advanced mathematics, this course is the right course for you. In this course, we build on previously defined notions of the integral of a single-variable function over an interval. Now, we will extend our understanding of integrals to work with functions of more than one variable. First, we will learn how to integrate a real-valued multivariable function over different regions in the plane. Then, we will introduce vector functions, which assigns a point to a vector. This will prepare us for our final course in the specialization on vector calculus. Finally, we will introduce techniques to approximate definite integrals when working with discrete data and through a peer reviewed project on, apply these techniques real world problems. This course continues your study of calculus by focusing on the applications of integration. The applications in this section have many common features. First, each is an example of a quantity that is computed by evaluating a definite integral. Second, the formula for that application is derived from Riemann sums. Rather than measure rates of change as we did with differential calculus, the definite integral allows us to measure the accumulation of a quantity over some interval of input values. This notion of accumulation can be applied to different quantities, including money, populations, weight, area, volume, and air pollutants. The concepts in this course apply to many other disciplines outside of traditional mathematics.
We will expand the notion of the average value of a data set to allow for infinite values, develop the formula for arclength and curvature, and derive formulas for velocity, acceleration, and areas between curves. Through examples and projects, we will apply the tools of this course to analyze and model real world data. This course continues your study of calculus by focusing on the applications of integration to vector valued functions, or vector fields. These are functions that assign vectors to points in space, allowing us to develop advanced theories to then apply to real-world problems. We define line integrals, which can be used to fund the work done by a vector field. We culminate this course with Green's Theorem, which describes the relationship between certain kinds of line integrals on closed paths and double integrals. In the discrete case, this theorem is called the Shoelace Theorem and allows us to measure the areas of polygons. We use this version of the theorem to develop more tools of data analysis through a peer reviewed project. Upon successful completion of this course, you have all the tools needed to master any advanced mathematics, computer science, or data science that builds off of the foundations of single or multivariable calculus.
|
4 course series
|
Intermediate level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/integral-calculus-data-modeling
| null |
968 |
Chemerinsky on Constitutional Law – Individual Rights and Liberties
|
12,093
|
4.9
| 78 |
Erwin Chemerinsky
|
University of California, Irvine
|
[]
|
Chemerinsky on Constitutional Law: Individual Rights and Liberties will highlight the construction and interpretation of the U.S. Constitution through the centuries with an emphasis on protections of individual liberties and the evolution of equal protection. You'll learn the history behind the Constitution, cases that formed important precedent, and how changes in interpretation have been dependent on shifts in cultural and political climate as well as the composition of the Supreme Court. In this course we will investigate the protection of individual rights and liberties and take a look at what rights are and are not protected and investigate several important shifts in jurisprudence. We'll begin by examining the structure of the Constitution's protection of individual rights. We'll then examine the circumstances under which, various rights and liberties can be regulated by the federal, state, and local government. We'll examine when the government can permissibly treat people unequally and when it can't. In our final two lectures, we'll take a close look at what is probably the most famous amendment to the Constitution, the First Amendment.
Join me as we look at the questions both raised and answered by the Constitution and those that interpret it!
By the end of this course, you should be able to:
- Describe the individual liberties protected by the Constitution and account for the history and structure of their protection
- Illustrate compromises found in the Constitution by citing examples and historic background
- Articulate the importance of key cases such as Brown v. Board, Lemon v. Kurtzman, and Lochner v. New York
- Explain how the outcome of cases is often dependent upon the current cultural and political climate as well as the composition of the court by citing particular cases and important shifts in the court's jurisprudence
- Assess the relative suitability of various approaches to constitutional interpretation and analysis 1 video3 readings How are individual rights protected? In this module we’ll take a look at three of the structures that protect our individual liberties: the state action doctrine, the application of the bill of rights to the states, and the levels of scrutiny principle. 3 videos1 reading1 quiz What rights are enumerated in the Constitution? How has the court's understanding and protection of these rights evolved? In this lecture we'll become familiar with the rights that are both specifically enumerated and implied by the text of the Constitution. 8 videos1 reading1 quiz1 peer review In this module we’ll examine how equal protection has been applied to different suspect classifications such as race, gender, citizenship, and more. In addition, we will consider how the court has used levels of scrutiny in order to determine when the government can permissibly discriminate based upon suspect classifications. 7 videos1 reading1 quiz1 peer review Why is freedom of speech protected as a fundamental right? What is its importance? In this module we’ll review four possible answers to this question. We’ll also examine the basic principles that guide the Supreme Court’s methodology when examining questions of free speech. Finally, we’ll take a look at the types of speech that have not been traditionally protected and the limitations that can be imposed on where protected forms of speech can be exercised. 4 videos1 reading1 quiz1 peer review In our final lecture module, we’ll briefly examine the Lemon Test, named after the Lemon v. Kurtzman case in which it was first articulated, to see how the court has evaluated cases regarding the Establishment Clause. We’ll also take a look at how the court decides questions regarding the Free Exercise Clause. 1 video1 reading1 quiz1 peer review As the course draws to a final close, we would like to thank you for your participation. 2 readings
|
7 modules
|
Beginner level
|
16 hours to complete (3 weeks at 5 hours a week)
|
https://www.coursera.org/learn/chemerinsky-individual-rights
| null |
969 |
Energy Production, Distribution & Safety Specialization
|
56,539
|
4.7
| 5,833 |
Tom Russo
|
The State University of New York
|
[]
|
This specialization provides introductory knowledge about the energy industry and associated career opportunities, whether you are interested in a utility technician or utility worker role, or emerging green energy solutions. It is intended for those considering a career in the field, and people already working in the industry who have less than three years of experience and have not completed similar training. Through four courses, learners receive an overview of electric power systems, natural gas, safety practices, and the energy industry as a whole. To learn more, please watch the overview video by copying and pasting the following link into your web browser:https://www.youtube.com/watch?time_continue=2&v=2Yh9qIYiUDkOpens in a new tab. Applied Learning Project Participants engage in exploratory opportunities and preparatory steps, creating a roadmap to achieve personal goals related to an energy industry career. The result is a tangible artifact for participants to include in their professional portfolio and leverage relevant prospects. This course familiarizes you with standards and policies of the electric utility industry, and provides you with basic vocabulary used in the business. It introduces the electric power system, from generation of the electricity all the way to the wall plug. You will learn about the segments of the system, and common components like power cables and transformers. This course is for individuals considering a career in the energy field (who have a high school diploma, at minimum, and basic knowledge of mathematics), and existing energy sector employees with less than three years of experience who have not completed similar training and would benefit from a course of foundational industry concepts.
The course is a combination of online lectures, videos, readings and discussions.
This is the first course in the Energy Production, Distribution & Safety specialization that explores various facets of the power sector, and features a culminating project involving creation of a roadmap to achieve a self-established, energy-related professional goal. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=2Yh9qIYiUDk. This course will educate you in the characteristics and properties of natural gas, preparing you with the ability to summarize gas system components and new pipeline technologies. You will be enabled to grasp the key factors behind formation of the natural gas industry and the historical use of natural gas. Ultimately, you will be able to identify gas and carbon monoxide safety procedures. This course is for individuals considering a career in the energy field (who have a high school diploma, at minimum, and basic knowledge of mathematics), and existing energy sector employees with less than three years of experience who have not completed similar training and would benefit from a course of foundational industry concepts.
Main concepts of this course will be delivered through lectures, readings, discussions and various videos.
This is the second course in the Energy Production, Distribution & Safety specialization that explores various facets of the power sector, and features a culminating project involving creation of a roadmap to achieve a self-established, energy-related professional goal. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=2Yh9qIYiUDk. This course arms you with basic utility industry safety knowledge. You will be educated about personal protective equipment, fire safety, hazardous materials and their symbols. You will gain insights to recognize the importance of a safe work environment. This course is for individuals considering a career in the energy field (who have a high school diploma, at minimum, and basic knowledge of mathematics), and existing energy sector employees with less than three years of experience who have not completed similar training and would benefit from a course of foundational industry concepts.
The course is a combination of online lectures, videos, readings and discussions.
This is the third course in the Energy Production, Distribution & Safety specialization that explores various facets of the power sector, and features a culminating project involving creation of a roadmap to achieve a self-established, energy-related professional goal. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=2Yh9qIYiUDk. This course provides a broad view of the evolving nature of energy and the influence of cost, availability, sustainability, technical advancements, lifestyle, and concern over the environment. Learners get a peek into our energy history, recent technical and societal advancements in clean energy, and some of the more important adjustments we have seen and will continue to see. It includes a discussion of how our energy infrastructure adapts to the changing landscape while managing costs, often deploying a new workforce while providing highly reliable grid power necessary for a robust and competitive economy. Material covers current and future workforce opportunities. This course is for individuals considering a career in the energy field (who have a high school diploma, at minimum, and basic knowledge of mathematics), and existing energy sector employees with less than three years of experience who have not completed similar training and would benefit from a course of foundational industry concepts.
The course is a combination of online lectures, videos, readings and discussions.
This is the fourth course in the Energy Production, Distribution & Safety specialization that explores various facets of the power sector, and features a culminating project involving creation of a roadmap to achieve a self-established, energy-related professional goal. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=2Yh9qIYiUDk.
|
4 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/energy-industry
| null |
970 |
Object-Oriented Design
|
128,178
|
4.7
| 2,318 |
Kenny Wong
|
University of Alberta
|
['Object-Oriented Design', 'Object-Oriented Analysis And Design', 'Unified Modeling Language (UML)']
|
This course takes Java beginners to the next level by covering object-oriented analysis and design. You will discover how to create modular, flexible, and reusable software, by applying object-oriented design principles and guidelines. And, you will be able to communicate these designs in a visual notation known as Unified Modelling Language (UML). You will be challenged in the Capstone Project to apply your knowledge of object-oriented design by evolving and documenting the Java codebase for an Android application with corresponding UML documentation.
After completing this course, you will be able to:
• Apply the Class Responsibility Collaborator (CRC) technique to analyze and design the object-oriented model for a problem.
• Explain and apply object-oriented modeling principles and their purpose (e.g., abstraction, encapsulation, decomposition, generalization).
• Explain and apply different types of inheritance
• Explain the difference between association, aggregation, and composition dependencies.
• Express object-oriented models as Unified Modeling Language (UML) class diagrams.
• Translate between UML class diagrams and equivalent Java code.
• Apply design guidelines for modularity, separation of concerns, information hiding, and conceptual integrity to create a flexible, reusable, maintainable design.
• Explain the tradeoff between cohesion and coupling. Good software design begins before coding. After establishing the initial software requirements, design practices involve two main activities: conceptual design and technical design. In this module, you will realize the importance of design and object-oriented thinking, and learn how to design software using techniques like CRC cards. 6 videos9 readings4 assignments Best software design practices have evolved alongside programming languages. Today, all developers should be familiar with abstraction, encapsulation, decomposition, and generalization, which are fundamental principles in object-oriented design. You will learn all of these principles and how they are expressed in Java and communicated visually in Unified Modelling Language. 11 videos4 readings1 assignment2 peer reviews Additional design principles will help you to create code that is flexible, reusable, and maintainable. In this module you will learn about coupling and cohesion, separation of concerns, information hiding, and conceptual integrity. You will also learn to avoid common pitfalls with inheritance, and ways to express software behavior in UML. 8 videos6 readings1 assignment4 peer reviews In the previous modules you were introduced to object-oriented analysis and design, object-oriented modeling, and design principles. To cement your understanding of this material, you created a UML class diagram from an example Android code base, and used your understanding of the code base to make sequence and state diagrams to model its behavior. Now, in the final module of the course, given a description of new functionality and an updated UML class diagram, you will implement the updated design into the Android code base. After completing this development task, you will be ready to complete the final exam. 4 readings1 assignment1 peer review
|
4 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/object-oriented-design
|
93%
|
971 |
Automated Report Generation with Generative AI
|
Enrollment number not found
|
4.0
| 31 |
Arkadi Avanesyan
|
Coursera Instructor Network
|
['Decision-Making based on AI solutions', 'Awareness of Emerging Technologies', 'Data Accuracy and Technical Proficiency', 'Productivity Improvement', 'Automated Reporting Proficiency']
|
In today's data-driven world, generating reports efficiently is a valuable skill for professionals across various industries. This course introduces beginners to the world of automated report generation using AI-powered tools and techniques. You will learn how to leverage the capabilities of artificial intelligence to streamline the reporting process, save time, and improve data accuracy. By the end of this course, you will not only grasp foundational concepts but also have the skills to streamline your personal and professional life; whether it's tracking and reporting on your personal finances, health and wellness, home energy efficiency, or implementing automated reporting solutions for your company's sales or marketing, saving valuable time and resources while improving data accuracy and decision-making. Moreover, you'll have the knowledge and confidence to explore automation opportunities within your workplace, making you an asset in the digital transformation era.
Upon completing this course, learners can utilize AI-driven tools to generate automated reports, thereby improving productivity and data accuracy in their respective fields.
Audience: Office Professionals, Consultants, Students, Small Business Owners, Reporting and Automation Enthusiasts
To fully benefit from the " Introduction to Automated Report Generation with AI " course, learners should have basic computer skills, familiarity with software, an interest in data, analytics, and reporting, and access to a computer or device for practice. In today's data-driven world, the ability to generate reports efficiently is a valuable skill for professionals across various industries. This course introduces beginners to the world of automated report generation using AI powered tools and techniques. You will learn how to leverage the capabilities of artificial intelligence to streamline the reporting process, save time, and improve data accuracy. 12 videos6 readings1 assignment1 ungraded lab
|
1 module
|
Beginner level
|
2 hours to complete
|
https://www.coursera.org/learn/automated-report-generation-with-generative-ai
| null |
972 |
Speaking Skills for University Success
|
12,889
|
4.8
| 100 |
Marla Yoshida
|
University of California, Irvine
|
[]
|
As a student in an English-speaking university, you’ll need to speak in many situations, both formal and informal, planned and spontaneous. In this course, you’ll get advice for speaking in many different situations. You’ll learn how to prepare for an academic discussion with classmates and how to lead a discussion effectively. You’ll learn about how to work smoothly in group projects—a popular type of assignment in many university classes—and what to say in small talk with classmates or others. You’ll learn how to give an unplanned, impromptu speech and also how to plan and deliver a formal presentation in class. Speaking in any of these situations can be a bit intimidating, but if you know what to do and practice whenever the opportunity arises, it will become easier, and you can become a more confident and successful speaker. In this first week of the course, we’ll be talking about academic discussions—the situations when you’ll be talking about an academic topic with a group of classmates. You’ll learn how to prepare for a discussion by gathering background knowledge and how to lead a discussion and encourage everyone to participate. You’ll also learn how to help your discussion go smoothly and how to handle disagreements, which are bound to arise in any discussion. Finally, you’ll practice by watching a video of an academic discussion and rating its strong and weak points. Let’s begin! 7 videos1 reading1 assignment This week you’ll learn about several situations that require informal communication. First you’ll hear how you can work more smoothly in group projects, which have become a very common type of assignment in university work. You’ll learn about the importance of small talk—all those casual conversations with friends or strangers that lead to smoother communication—and learn which topics to talk about and which ones to avoid. You’ll hear some tips for times when you need to speak without having a chance to prepare, and record your impromptu speaking practice to share with other students. So let’s get started with informal speaking 4 videos1 reading2 assignments1 peer review This week we’ll start thinking about presentations—those assignments when you’ll have time to prepare a speech and present it in front of a class. You’ll learn about the parts of a presentation and what elements should be included in each one. You’ll think about how to catch the listeners’ interest and introduce your main idea in the introduction, how to give more details to support your ideas in the body, and how to wrap it all up in a “fireworks” conclusion. You’ll practice by watching and evaluating a presentation on an academic topic. Let’s get ready to give a great presentation! 4 videos2 readings1 assignment In this last week of the course, you’ll hear some advice about how to give the presentation that you’ve planned so carefully. You’ll hear some tips for how to rehearse your speech so that you can deliver it smoothly, and you’ll learn some basic principles for preparing attractive slides to go along with your speech and presenting them well. You’ll also hear some suggestions for speaking effectively by using both the power of your voice and effective body language. You’ll practice by playing around with the arrangement of elements on some slides, and you’ll analyze the presentation style of a speaker in a recorded speech. So let’s begin! 4 videos2 readings1 assignment1 discussion prompt
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/speaking-skills-for-university-success
|
95%
|
973 |
AIDS: Fear and Hope
|
15,006
|
4.8
| 420 |
Richard Meisler, Ph.D.
|
University of Michigan
|
['AIDS', 'healthcare', 'Public Health', 'HIV']
|
The basic biology of the virus, HIV, and the disease it causes, AIDS. The economic, social and political factors that determine who gets sick and who remains healthy, who lives and who dies. The progress of scientific research and medical treatments. The reasons for hope; the reasons for fear. (To get a glimpse of some of the materials that students have been posting on the course forums, go to @AIDSFAH or #AIDSFAH.) HIV Basics, Stigma, Three Books, Chimps to Humans, Some Memories 9 videos6 readings1 assignment Transmission, Gender, More Memories 7 videos1 reading1 assignment The Critical Issue--Testing 9 videos1 reading1 assignment Not a death sentence, but not easy; More Politics, Sexual Orientation 5 videos1 reading1 assignment Doctors, Medication, More Politics, More Memories 7 videos1 reading1 assignment 8 videos1 reading1 assignment Cure? Legal Issues, Cost, The Future, Acting Up 10 videos3 readings1 assignment
|
7 modules
|
Beginner level
| null |
https://www.coursera.org/learn/aids-fear-hope
|
99%
|
974 |
Responsible Generative AI Specialization
|
Enrollment number not found
|
4.9
| 41 |
Merve Hickok
|
University of Michigan
|
['Generative AI Strategy', 'Responsible Generative AI', 'Risk Management', 'Generative AI', 'Generative AI Labor', 'Generative AI Governance', 'Strategy', 'Leadership and Management', 'Future of Work']
|
“Responsible Generative AI” is a Specialization exploring the possibilities and risks of generative artificial intelligence (AI). You will establish a comprehensive understanding of the impact of this technology. The series will help you identify impacts relevant to business operations, consumers, society, the labor market, and the environment. Throughout each course, you’ll explore both the use cases and limitations of generative AI to explain business and societal considerations. This course series focuses on both new concerns stemming from this emerging technology and the amplification effects generative AI can have on existing concerns. By gaining a deeper understanding of responsible AI use, you’ll be able to make more informed decisions about the development, use, and governance of generative AI systems within your organization. Applied Learning Project Learners will engage in discussion forums and be assessed through quizzes to demonstrate knowledge in the Responsible Generative AI Specialization. They will take away an expanded understanding of the concerns related to generative AI for informed decisions related to strategy, management, governance, labor, and risk management, including economic, reputational, compliance, and consumer risk. Understand the basics of generative AI Discuss the application of generative AI Describe the general risks associated with generative AI systems Understand the global nature of generative AI products and the diversity of its users Make informed business decisions regarding the impact and risks of generative AI systems Critically consider the different ways that generative AI impacts society Understand emerging governance expectations for businesses developing and implementing generative AI Identify relevant strategy considerations, costs, and key stakeholders for generative AI projects Apply responsible AI analysis to generative AI decisions Explore scenarios for the future of work Discuss the impact generative AI could have on labor and business Make informed assessments about labor involvement in generative AI technologies
|
4 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/responsible-generative-ai
| null |
975 |
Statistical Molecular Thermodynamics
|
25,169
|
4.9
| 354 |
Dr. Christopher J. Cramer
|
University of Minnesota
|
[]
|
This introductory physical chemistry course examines the connections between molecular properties and the behavior of macroscopic chemical systems. This module includes philosophical observations on why it's valuable to have a broadly disseminated appreciation of thermodynamics, as well as some drive-by examples of thermodynamics in action, with the intent being to illustrate up front the practical utility of the science, and to provide students with an idea of precisely what they will indeed be able to do themselves upon completion of the course materials (e.g., predictions of pressure changes, temperature changes, and directions of spontaneous reactions). The other primary goal for this week is to summarize the quantized levels available to atoms and molecules in which energy can be stored. For those who have previously taken a course in elementary quantum mechanics, this will be a review. For others, there will be no requirement to follow precisely how the energy levels are derived--simply learning the final results that derive from quantum mechanics will inform our progress moving forward. Homework problems will provide you the opportunity to demonstrate mastery in the application of the above concepts. 9 videos6 readings1 assignment This module begins our acquaintance with gases, and especially the concept of an "equation of state," which expresses a mathematical relationship between the pressure, volume, temperature, and number of particles for a given gas. We will consider the ideal, van der Waals, and virial equations of state, as well as others. The use of equations of state to predict liquid-vapor diagrams for real gases will be discussed, as will the commonality of real gas behaviors when subject to corresponding state conditions. We will finish by examining how interparticle interactions in real gases, which are by definition not present in ideal gases, lead to variations in gas properties and behavior. Homework problems will provide you the opportunity to demonstrate mastery in the application of the above concepts. 8 videos1 reading1 assignment This module delves into the concepts of ensembles and the statistical probabilities associated with the occupation of energy levels. The partition function, which is to thermodynamics what the wave function is to quantum mechanics, is introduced and the manner in which the ensemble partition function can be assembled from atomic or molecular partition functions for ideal gases is described. The components that contribute to molecular ideal-gas partition functions are also described. Given specific partition functions, derivation of ensemble thermodynamic properties, like internal energy and constant volume heat capacity, are presented. Homework problems will provide you the opportunity to demonstrate mastery in the application of the above concepts. 8 videos1 reading1 assignment This module connects specific molecular properties to associated molecular partition functions. In particular, we will derive partition functions for atomic, diatomic, and polyatomic ideal gases, exploring how their quantized energy levels, which depend on their masses, moments of inertia, vibrational frequencies, and electronic states, affect the partition function's value for given choices of temperature, volume, and number of gas particles. We will examine specific examples in order to see how individual molecular properties influence associated partition functions and, through that influence, thermodynamic properties. Homework problems will provide you the opportunity to demonstrate mastery in the application of the above concepts. 9 videos1 reading1 assignment This module is the most extensive in the course, so you may want to set aside a little extra time this week to address all of the material. We will encounter the First Law of Thermodynamics and discuss the nature of internal energy, heat, and work. Especially, we will focus on internal energy as a state function and heat and work as path functions. We will examine how gases can do (or have done on them) pressure-volume (PV) work and how the nature of gas expansion (or compression) affects that work as well as possible heat transfer between the gas and its surroundings. We will examine the molecular level details of pressure that permit its derivation from the partition function. Finally, we will consider another state function, enthalpy, its associated constant pressure heat capacity, and their utilities in the context of making predictions of standard thermochemistries of reaction or phase change. Homework problems will provide you the opportunity to demonstrate mastery in the application of the above concepts. 11 videos1 reading1 assignment This module introduces a new state function, entropy, that is in many respects more conceptually challenging than energy. The relationship of entropy to extent of disorder is established, and its governance by the Second Law of Thermodynamics is described. The role of entropy in dictating spontaneity in isolated systems is explored. The statistical underpinnings of entropy are established, including equations relating it to disorder, degeneracy, and probability. We derive the relationship between entropy and the partition function and establish the nature of the constant β in Boltzmann's famous equation for entropy. Finally, we consider the role of entropy in dictating the maximum efficiency that can be achieved by a heat engine based on consideration of the Carnot cycle. Homework problems will provide you the opportunity to demonstrate mastery in the application of the above concepts. 9 videos1 reading1 assignment This module is relatively light, so if you've fallen a bit behind, you will possibly have the opportunity to catch up again. We examine the concept of the standard entropy made possible by the Third Law of Thermodynamics. The measurement of Third Law entropies from constant pressure heat capacities is explained and is compared for gases to values computed directly from molecular partition functions. The additivity of standard entropies is exploited to compute entropic changes for general chemical changes. Homework problems will provide you the opportunity to demonstrate mastery in the application of the above concepts. 7 videos1 reading1 assignment This last module rounds out the course with the introduction of new state functions, namely, the Helmholtz and Gibbs free energies. The relevance of these state functions for predicting the direction of chemical processes in isothermal-isochoric and isothermal-isobaric ensembles, respectively, is derived. With the various state functions in hand, and with their respective definitions and knowledge of their so-called natural independent variables, Maxwell relations between different thermochemical properties are determined and employed to determine thermochemical quantities not readily subject to direct measurement (such as internal energy). Armed with a full thermochemical toolbox, we will explain the behavior of an elastomer (a rubber band, in this instance) as a function of temperature. Homework problems will provide you the opportunity to demonstrate mastery in the application of the above concepts. The final exam will offer you a chance to demonstrate your mastery of the entirety of the course material. 9 videos1 reading1 assignment This is the final graded exercise (20 questions) for the course. There is no time limit to take the exam. 1 assignment
|
9 modules
|
Beginner level
| null |
https://www.coursera.org/learn/statistical-thermodynamics
|
98%
|
976 |
Cloud Virtualization, Containers and APIs
|
13,781
|
4.4
| 114 |
Noah Gift
|
Duke University
|
[]
|
Welcome to the second course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn to design Cloud-native systems with the fundamental building blocks of Cloud computing. These building blocks include virtual machines and containers. You will also learn how to build effective Microservices using technologies like Flask and Kubernetes. Finally, you will analyze successful patterns in Operations including: Effective alerts, load testing and Kaizen. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you build a containerized Flask application that is continuously deployed to a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP). This week, you will learn how to access the free tiers of three Cloud environments. If you are joining after completing the first course in this Specialization, this will already be familiar to you. You will then have an opportunity to review the details of the final project in this course: Creating a containerized Flask application that is continuously deployed to a Cloud platform. Each week, you will learn and build upon key Cloud development skills to prepare you for this final course project. 5 videos4 readings1 discussion prompt This week, you will learn to evaluate the correct workflows for virtual machines and containers and how to choose the appropriate solution for the task at end. You will also learn about the powerful container management service: Kubernetes. You will apply this knowledge to create a containerized web service and deploy it to a managed container service. 26 videos16 readings4 assignments4 discussion prompts3 ungraded labs This week, you will learn to build effective Microservices that comply with DevOps best practices. You will also learn to operationalize Microservices using Continuous Delivery. You will apply this knowledge to create an effective Microservice using AWS Lambda. 22 videos16 readings4 assignments3 discussion prompts3 ungraded labs This week, you will learn to effectively perform Operations. This involves mastering Monitoring and Alerts. A key question about Monitoring and Alerts is what to do when they occur. This question is handled in the following lesson. You will learn how load testing can prevent issues before they arise. Finally, the topic of Kaizen, or continuous improvement, is tackled. All of the topics this week are components of DevOps best practices. 13 videos13 readings4 assignments3 discussion prompts4 ungraded labs
|
4 modules
|
Beginner level
|
31 hours to complete (3 weeks at 10 hours a week)
|
https://www.coursera.org/learn/cloud-virtualization-containers-api-duke
| null |
977 |
Basic Statistics
|
293,918
|
4.6
| 4,475 |
Matthijs Rooduijn
|
University of Amsterdam
|
['Statistics', 'Confidence Interval', 'Statistical Hypothesis Testing', 'R Programming']
|
Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression.
The second part of the course is concerned with the basics of probability: calculating probabilities, probability distributions and sampling distributions. You need to know about these things in order to understand how inferential statistics work.
The third part of the course consists of an introduction to methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in. We will discuss confidence intervals and significance tests.
You will not only learn about all these statistical concepts, you will also be trained to calculate and generate these statistics yourself using freely available statistical software. In this module we'll consider the basics of statistics. But before we start, we'll give you a broad sense of what the course is about and how it's organized. Are you new to Coursera or still deciding whether this is the course for you? Then make sure to check out the 'Course introduction' and 'What to expect from this course' sections below, so you'll have the essential information you need to decide and to do well in this course! If you have any questions about the course format, deadlines or grading, you'll probably find the answers here. Are you a Coursera veteran and ready to get started? Then you might want to skip ahead to the first course topic: 'Exploring data'. You can always check the general information later. Veterans and newbies alike: Don't forget to introduce yourself in the 'meet and greet' forum! 1 video11 readings1 assignment In this first module, we’ll introduce the basic concepts of descriptive statistics. We’ll talk about cases and variables, and we’ll explain how you can order them in a so-called data matrix. We’ll discuss various levels of measurement and we’ll show you how you can present your data by means of tables and graphs. We’ll also introduce measures of central tendency (like mode, median and mean) and dispersion (like range, interquartile range, variance and standard deviation). We’ll not only tell you how to interpret them; we’ll also explain how you can compute them. Finally, we’ll tell you more about z-scores. In this module we’ll only discuss situations in which we analyze one single variable. This is what we call univariate analysis. In the next module we will also introduce studies in which more variables are involved. 8 videos5 readings1 assignment3 app items In this second module we’ll look at bivariate analyses: studies with two variables. First we’ll introduce the concept of correlation. We’ll investigate contingency tables (when it comes to categorical variables) and scatterplots (regarding quantitative variables). We’ll also learn how to understand and compute one of the most frequently used measures of correlation: Pearson's r. In the next part of the module we’ll introduce the method of OLS regression analysis. We’ll explain how you (or the computer) can find the regression line and how you can describe this line by means of an equation. We’ll show you that you can assess how well the regression line fits your data by means of the so-called r-squared. We conclude the module with a discussion of why you should always be very careful when interpreting the results of a regression analysis. 8 videos6 readings1 assignment1 app item This module introduces concepts from probability theory and the rules for calculating with probabilities. This is not only useful for answering various kinds of applied statistical questions but also to understand the statistical analyses that will be introduced in subsequent modules. We start by describing randomness, and explain how random events surround us. Next, we provide an intuitive definition of probability through an example and relate this to the concepts of events, sample space and random trials. A graphical tool to understand these concepts is introduced here as well, the tree-diagram.Thereafter a number of concepts from set theory are explained and related to probability calculations. Here the relation is made to tree-diagrams again, as well as contingency tables. We end with a lesson where conditional probabilities, independence and Bayes rule are explained. All in all, this is quite a theoretical module on a topic that is not always easy to grasp. That's why we have included as many intuitive examples as possible. 11 videos5 readings1 assignment1 app item Probability distributions form the core of many statistical calculations. They are used as mathematical models to represent some random phenomenon and subsequently answer statistical questions about that phenomenon. This module starts by explaining the basic properties of a probability distribution, highlighting how it quantifies a random variable and also pointing out how it differs between discrete and continuous random variables. Subsequently the cumulative probability distribution is introduced and its properties and usage are explained as well. In a next lecture it is shown how a random variable with its associated probability distribution can be characterized by statistics like a mean and variance, just like observational data. The effects of changing random variables by multiplication or addition on these statistics are explained as well.The lecture thereafter introduces the normal distribution, starting by explaining its functional form and some general properties. Next, the basic usage of the normal distribution to calculate probabilities is explained. And in a final lecture the binomial distribution, an important probability distribution for discrete data, is introduced and further explained. By the end of this module you have covered quite some ground and have a solid basis to answer the most frequently encountered statistical questions. Importantly, the fundamental knowledge about probability distributions that is presented here will also provide a solid basis to learn about inferential statistics in the next modules. 8 videos5 readings1 assignment1 app item Methods for summarizing sample data are called descriptive statistics. However, in most studies we’re not interested in samples, but in underlying populations. If we employ data obtained from a sample to draw conclusions about a wider population, we are using methods of inferential statistics. It is therefore of essential importance that you know how you should draw samples. In this module we’ll pay attention to good sampling methods as well as some poor practices. To draw conclusions about the population a sample is from, researchers make use of a probability distribution that is very important in the world of statistics: the sampling distribution. We’ll discuss sampling distributions in great detail and compare them to data distributions and population distributions. We’ll look at the sampling distribution of the sample mean and the sampling distribution of the sample proportion. 7 videos5 readings1 assignment1 app item We can distinguish two types of statistical inference methods. We can: (1) estimate population parameters; and (2) test hypotheses about these parameters. In this module we’ll talk about the first type of inferential statistics: estimation by means of a confidence interval. A confidence interval is a range of numbers, which, most likely, contains the actual population value. The probability that the interval actually contains the population value is what we call the confidence level. In this module we’ll show you how you can construct confidence intervals for means and proportions and how you should interpret them. We’ll also pay attention to how you can decide how large your sample size should be. 7 videos4 readings1 assignment1 app item In this module we’ll talk about statistical hypotheses. They form the main ingredients of the method of significance testing. An hypothesis is nothing more than an expectation about a population. When we conduct a significance test, we use (just like when we construct a confidence interval) sample data to draw inferences about population parameters. The significance test is, therefore, also a method of inferential statistics. We’ll show that each significance test is based on two hypotheses: the null hypothesis and the alternative hypothesis. When you do a significance test, you assume that the null hypothesis is true unless your data provide strong evidence against it. We’ll show you how you can conduct a significance test about a mean and how you can conduct a test about a proportion. We’ll also demonstrate that significance tests and confidence intervals are closely related. We conclude the module by arguing that you can make right and wrong decisions while doing a test. Wrong decisions are referred to as Type I and Type II errors. 7 videos4 readings1 assignment1 app item This is the final module, where you can apply everything you've learned until now in the final exam. Please note that you can only take the final exam once a month, so make sure you are fully prepared to take the test. Please follow the honor code and do not communicate or confer with others while taking this exam. Good luck! 1 assignment
|
9 modules
|
Beginner level
| null |
https://www.coursera.org/learn/basic-statistics
|
96%
|
978 |
Configure SIEM Security Operation using Microsoft Sentinel
|
Enrollment number not found
|
Rating not found
| null |
Microsoft
|
Microsoft
|
['Data Visualization and Analysis', 'Cloud Security Configuration', 'Automated Security Response Creation', 'Analytics Rule Deployment', 'SIEM and SOAR Application']
|
Upon completion of this course, you will be adequately prepared to take Microsoft's Configure SIEM security operations using Microsoft Sentinel Applied Skill assessment. This course covers all necessary content and provides essential practice to boost your confidence and ensure success in the final assessment. Did you know that by 2025, the world will be spending $10.5 trillion annually on cybersecurity damages? And without adequate cybersecurity, the risks hold devastating consequences.
This Short Course was created to empower IT professionals, security analysts, and system administrators to master Microsoft Sentinel to enhance their organization's security posture against evolving cyber threats.
By completing this short course, you'll gain the skills to configure and manage Security Information and Event Management (SIEM) operations using Microsoft Sentinel and become industry-ready to implement real-world cybersecurity solutions at work.
In this 3-hour-long course, you will learn how to understand the prerequisites for setting up Microsoft Sentinel, creating and configuring a Microsoft Sentinel workspace, and deploying a Microsoft Sentinel Content Hub Solution.
Combining theoretical knowledge with practical, hands-on exercises makes this course unique and will provide you with authentic, real-world scenarios. To be successful in this course, a foundational understanding of cloud computing, cybersecurity principles, and familiarity with Microsoft Azure is recommended. Upon completing this course, you will be able to configure and manage Security Information and Event Management (SIEM) operations using Microsoft Sentinel, encompassing workspace setup, content solution deployment, analytics, workbooks and basic automation to enhance organizational security posture. 1 video1 reading By the end of this lesson, you will be able to effectively set up Microsoft Sentinel within your organization's Azure environment. This lesson covers the essential prerequisites and permissions needed to deploy Microsoft Sentinel as it guides you through critical steps and important aspects of setting up and configuring the system for successful SIEM operations. 1 video2 readings1 assignment By the end of this lesson, you will have set up the foundational structure needed to use Microsoft Sentinel in your Azure environment. The lesson will walk you through the step-by-step process of establishing a Microsoft Sentinel workspace. This includes assigning roles, creating a dedicated resource group, and configuring a Log Analytics workspace. 1 video1 reading1 assignment In this lesson, you will learn to leverage the Content Hub for streamlining the discovery, deployment, and management of Microsoft Sentinel solutions. The Content Hub, which replaces the solutions gallery, provides a single platform for implementing ready-made solutions like data connectors, analytic rules, and playbooks to improve your security operations. We will specifically focus on how to deploy solutions from the Content Hub, using the Azure Activity data connector as a primary example. 1 video1 reading1 assignment In this lesson, you will receive step-by-step demonstrations on how to properly implement and manage crucial security and operational features in Microsoft Sentinel. You will learn to set up analytics rules, workbooks, and basic automation. The lesson will cover the essential skills needed for effective monitoring, analysis, and responses to security threats. By the end of this lesson, you will be capable of streamlining processes and improving security response capabilities within a Microsoft Sentinel environment. 3 videos6 readings2 assignments
|
5 modules
|
Intermediate level
|
3 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/configure-siem-security-operation-using-microsoft-sentinel
| null |
979 |
Stages of Incident Response
|
4,120
|
4.6
| 64 |
Keatron Evans
|
Infosec
|
['Continuous Function', 'Verification And Validation (V&V)', 'Ordered Pair', 'Representational State Transfer (REST)']
|
The Cyber Incident Response course will give students an understanding of how incidents are responded to at a high level, as well as allow them to build important technical skills through the hands-on labs and projects. This course starts with a high-level discussion of what happens at each phase of responding to an incident, followed by a technical deep dive into some of the more exciting parts of memory, network, and host analysis and forensics. This course is for anyone wishing to apply learned forensics and offensive knowledge such as ethical hacking to the incident response process. The Preparation section of the module goes into some detail with common definitions and severity criteria, with special attention being paid to making sure the student understands that the severity criteria should be based on overall organizational definitions and procedures. The latter part of the module goes into the importance of asset inventory and identification as a basis for establishing severity criteria. All these pieces are required for proper preparation for any incident. 3 videos1 reading The Identification section deals specifically with how incidents are identified, as well as the classification levels that incidents might fall within. It also reminds the student that these classification levels are established with input from upper management and the rest of the organization. We go into details of notifying the appropriate parties of the incident and how to do that properly. We end this course with a discussion of common tools and techniques. 4 videos1 reading This section explores containment and the proper scoping and management of it. We examine the details of how to contain an incident and, more importantly, how to define what containment means. We also explore common containment tools. 4 videos1 reading In the Investigation segment, you’ll learn the questions asked in normal investigations and how to properly answer them. You’ll explore the important data sources these answers are pulled from and the role this process plays in incident response overall. 3 videos1 reading Dive into what it takes to remove threats from and environment after the threat has been contained. We’ll also take a look at how to verify the threat has been eradicated and address proper notification of eradication to other authorized parties. Lastly, we’ll discuss some common tools for eradication. 4 videos1 reading This Recovery segment shows how we tie directly into business continuity and disaster recovery at this phase. We deal with how to restore systems in the least disruptive and most efficient way, as well as defining what constitutes "recovered." 4 videos1 reading Look at validation and sign-off of recovery. The module looks at how to effectively assess how well the team responded. It also looks at implementing needed improvements and how to ingest feedback from the rest of the organization or even outside organizations. 3 videos1 reading1 assignment
|
7 modules
|
Beginner level
|
4 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/stages-of-incident-response
| null |
980 |
Visual Analytics with Tableau
|
72,025
|
4.6
| 1,827 |
Suk S. Brar, M.B.A.
|
University of California, Davis
|
['Visual Analytics', 'Map', 'Tableau Software', 'Data Visualization']
|
In this third course of the specialization, we’ll drill deeper into the tools Tableau offers in the areas of charting, dates, table calculations and mapping. We’ll explore the best choices for charts, based on the type of data you are using. We’ll look at specific types of charts including scatter plots, Gantt charts, histograms, bullet charts and several others, and we’ll address charting guidelines. We’ll define discrete and continuous dates, and examine when to use each one to explain your data. You’ll learn how to create custom and quick table calculations and how to create parameters. We’ll also introduce mapping and explore how Tableau can use different types of geographic data, how to connect to multiple data sources and how to create custom maps. In this module, you will explore the topic of charting in Tableau. By now you should already be well versed in how to change colors, shapes, and sizes of charts, so we are going to practice and demonstrate that skill more. You will be able to explain what the Tableau Tooltip does and when to use it. You will be able to discuss the various guidelines for choosing the right chart for your data. You will also create a chart using Tableau. 10 videos2 readings1 assignment1 peer review This module highlights the important topic of dates within Tableau. You will be able to differentiate between discrete and continuous dates and when to use each. You will be able to use date hierarchies and use the date field to better customize your charts. You will be able to convert between discrete and continuous dates and know when and why you want to switch from one to the other. You will create dates using calculated fields. 5 videos1 assignment1 peer review In this module, you will focus on table calculations. You will be able to create new calculated fields to allow you to compare fields, apply aggregations, and more. You will be able use quick table calculations and create new calculated fields. You will be able to customize them and apply filters and parameters to your table calculations. 6 videos1 assignment1 peer review In this final module, we will go more in depths about maps within Tableau. You will be able to connect to a different data sources and customize your maps by changing colors, shapes, and sizes. You will be able to custom geocode a map and create Tableau maps with geographic data that is not recognized by Tableau. You will also be able to create dual layer maps and showcase how to overlay maps on top of one another. 7 videos1 assignment1 peer review1 discussion prompt
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/dataviz-visual-analytics
|
88%
|
981 |
Object Oriented Java Programming: Data Structures and Beyond Specialization
|
74,337
|
4.7
| 3,378 |
Leo Porter
|
University of California San Diego
|
['Data Structure', 'Problem Solving', 'Java Programming', 'Object-Oriented Programming (OOP)']
|
This Specialization covers intermediate topics in software development. You’ll learn object-oriented programming principles that will allow you to use Java to its full potential, and you’ll implement data structures and algorithms for organizing large amounts of data in a way that is both efficient and easy to work with. You’ll also practice critically evaluating your own code, and you’ll build technical communication skills that will help you prepare for job interviews and collaborative work as a software engineer. In the final Capstone Project, you’ll apply your skills to analyze data collected from a real-world (social) network. Google has contributed real-world projects and the involvement of its engineers as guest lecturers to these courses. A small, select group of top learners who complete the Specialization will be offered practice interviews with Google recruiters. Invitation to a practice interview does not guarantee an actual interview or employment. Welcome to our course on Object Oriented Programming in Java using data visualization. People come to this course with many different goals -- and we are really excited to work with all of you! Some of you want to be professional software developers, others want to improve your programming skills to implement that cool personal project that you’ve been thinking about, while others of you might not yet know why you’re here and are trying to figure out what this course is all about. This is an intermediate Java course. We recommend this course to learners who have previous experience in software development or a background in computer science. Our goal is that by the end of this course each and every one of you feels empowered to create a Java program that’s more advanced than any you have created in the past and that is personally interesting to you. In achieving this goal you will also learn the fundamentals of Object Oriented Programming, how to leverage the power of existing libraries, how to build graphical user interfaces, and how to use some core algorithms for searching and sorting data. And this course is project-based, so we’ll dive right into the project immediately!
We are excited to be offering a unique course structure, designed to support learners of different backgrounds in succeeding at their own pace. The first module explains how this will work and if this course is right for you. We also recommend taking a few minutes to explore the course site. A good place to start is the navigation bar on the left. Click Course Content to see what material we’ll cover each week, as well preview the assignments you’ll need to complete to pass the course. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. Be sure to introduce yourself to everyone in the Meet and Greet forum.
This course should take about 6 weeks to complete. You can check out the recommended course schedule below to see a quick overview of the lessons and assignments you’ll complete each week.
We’re excited you’re here learning with us. Let’s get started! How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? This is an intermediate Java course. We recommend this course to learners who have previous experience in software development or a background in computer science, and in particular, we recommend that you have taken the first course in this specialization (which also requires some previous experience with Java).
In this course, you will use and analyze data structures that are used in industry-level applications, such as linked lists, trees, and hashtables. You will explain how these data structures make programs more efficient and flexible. You will apply asymptotic Big-O analysis to describe the performance of algorithms and evaluate which strategy to use for efficient data retrieval, addition of new data, deletion of elements, and/or memory usage.
The program you will build throughout this course allows its user to manage, manipulate and reason about large sets of textual data. This is an intermediate Java course, and we will build on your prior knowledge. This course is designed around the same video series as in our first course in this specialization, including explanations of core content, learner videos, student and engineer testimonials, and support videos -- to better allow you to choose your own path through the course! How does Google Maps plan the best route for getting around town given current traffic conditions? How does an internet router forward packets of network traffic to minimize delay? How does an aid group allocate resources to its affiliated local partners? To solve such problems, we first represent the key pieces of data in a complex data structure. In this course, you’ll learn about data structures, like graphs, that are fundamental for working with structured real world data. You will develop, implement, and analyze algorithms for working with this data to solve real world problems. In addition, as the programs you develop in this course become more complex, we’ll examine what makes for good code and class hierarchy design so that you can not only write correct code, but also share it with other people and maintain it in the future.
The backbone project in this course will be a route planning application. You will apply the concepts from each Module directly to building an application that allows an autonomous agent (or a human driver!) to navigate its environment. And as usual we have our different video series to help tie the content back to its importance in the real world and to provide tiered levels of support to meet your personal needs. You’ve hit a major milestone as a computer scientist and are becoming a capable programmer. You now know how to solve problems, write algorithms, and analyze solutions; and you have a wealth of tools (like data structures) at your disposal. You may now be ready for an internship or (possibly) an entry-level software engineering job. But can you land the internship/job? It depends in part on how well you can solve new technical problems and communicate during interviews. How can you get better at this? Practice! With the support of Google’s recruiting and engineering teams we’ve provided tips, examples, and practice opportunities in this course that may help you with a number of tech companies. We’ll assist you to organize into teams to practice. Lastly, we’ll give you basic job search advice, and tips for succeeding once you’re on the job. In this capstone project we’ll combine all of the skills from all four specialization courses to do something really fun: analyze social networks! The opportunities for learning are practically endless in a social network. Who are the “influential” members of the network? What are the sub-communities in the network? Who is connected to whom, and by how many links? These are just some of the questions you can explore in this project.
We will provide you with a real-world data set and some infrastructure for getting started, as well as some warm up tasks and basic project requirements, but then it’ll be up to you where you want to take the project. If you’re running short on ideas, we’ll have several suggested directions that can help get your creativity and imagination going. Finally, to integrate the skills you acquired in course 4 (and to show off your project!) you will be asked to create a video showcase of your final product.
|
5 course series
|
Intermediate level
|
4 months (at 10 hours a week)
|
https://www.coursera.org/specializations/java-object-oriented
| null |
982 |
Python Essentials for MLOps
|
20,273
|
4.2
| 192 |
Noah Gift
|
Duke University
|
['Python Programming', 'Information Engineering', 'Machine Learning', 'Test Automation', 'MLOps']
|
Python Essentials for MLOps (Machine Learning Operations) is a course designed to provide learners with the fundamental Python skills needed to succeed in an MLOps role. This course covers the basics of the Python programming language, including data types, functions, modules and testing techniques. It also covers how to work effectively with data sets and other data science tasks with Pandas and NumPy. Through a series of hands-on exercises, learners will gain practical experience working with Python in the context of an MLOps workflow. By the end of the course, learners will have the necessary skills to write Python scripts for automating common MLOps tasks. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their Python skills. In this module, you will learn how to effectively use variables, logic, and Python’s data structures to load, persist, and iterate over data. You will apply these data structures to solve different problems as well as extract data from them. 19 videos12 readings4 assignments2 discussion prompts4 ungraded labs In this module, you will learn how to create functions, classes, and methods. These are the basis of almost any program you might create with Python. Functions and classes are useful for organizing code, increasing maintainability and code reuse. 17 videos12 readings5 assignments5 ungraded labs In this module, you will learn the basics of Python testing. From a brief overview of the standard library to using a more modern approach with Pytest, one of the most popular testing libraries in Python. By the end of this module, you should be comfortable working with existing tests, creating new tests, and debugging test failures. 17 videos6 readings4 assignments3 ungraded labs In this module, you will learn how to work with data using Pandas and NumPy. From loading and reading datasets from different sources to plotting graphs and exploring common problems in data. Pandas will allow you to perform transformations and export your data into different formats, and NumPy will boost your ability to work with numerical data. 17 videos6 readings4 assignments3 ungraded labs In this module, you’ll grasp the basics of how to create and use APIs with Python using HTTP and command-line tools. We’ll go through all the details you need to know to create your own command-line tools and HTTP APIs to expose Machine Learning models. 22 videos8 readings4 assignments4 ungraded labs
|
5 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/python-mlops-duke
|
92%
|
983 |
Analyzing Big Data with SQL
|
27,185
|
4.8
| 526 |
Ian Cook
|
Cloudera
|
['Big Data', 'Data Analysis', 'Apache Impala', 'SQL', 'Apache Hive']
|
In this course, you'll get an in-depth look at the SQL SELECT statement and its main clauses. The course focuses on big data SQL engines Apache Hive and Apache Impala, but most of the information is applicable to SQL with traditional RDBMs as well; the instructor explicitly addresses differences for MySQL and PostgreSQL. By the end of the course, you will be able to
• explore and navigate databases and tables using different tools;
• understand the basics of SELECT statements;
• understand how and why to filter results;
• explore grouping and aggregation to answer analytic questions;
• work with sorting and limiting results; and
• combine multiple tables in different ways.
To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements:
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work)
• 64-bit operating system (32-bit operating systems will not work)
• 8 GB RAM or more
• 25GB free disk space or more
• Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled;
on Windows and Linux computers, you might need to enable it in the BIOS)
• For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work) 9 videos5 readings2 assignments1 discussion prompt 16 videos4 readings2 assignments1 discussion prompt 14 videos6 readings2 assignments1 discussion prompt 15 videos6 readings2 assignments2 discussion prompts 14 videos1 reading2 assignments1 discussion prompt 12 videos5 readings2 assignments1 peer review1 discussion prompt
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/cloudera-big-data-analysis-sql-queries
|
95%
|
984 |
Introduction to Java and Object-Oriented Programming
|
35,817
|
4.4
| 302 |
Brandon Krakowsky
|
University of Pennsylvania
|
['Unit Testing', 'Java Syntax', 'Java Programming', 'Object-Oriented Programming (OOP)', 'Java Tools']
|
This course provides an introduction to the Java language and object-oriented programming, including an overview of Java syntax and how it differs from a language like Python. Students will learn how to write custom Java classes and methods, and how to test their code using unit testing and test-driven development. Topics include basic data structures like Arrays and ArrayLists and overloading methods. Welcome to Java! This first module provides an introduction to the Java language and object-oriented programming. It includes an overview of Java syntax, in particular, how it differs from a language like Python. Topics will include variables and data types, loops and conditionals, printing to the console, scanning for user input, and code documentation. This module also explains the structure and inner-workings of a Java class and teaches you how to define your own custom classes and methods. 38 videos10 readings3 assignments2 app items In this module, you will be taught to test your code to get it working. The best way to do this is to write a set of unit tests that you can run against your program, at any time. In this module, we'll learn how to do unit testing in Java, and why we want to do it. We’ll also learn all about Java Arrays, which are collections of items, and ArrayLists, which are kind of like arrays, but much more flexible. These work just like lists in Python. ArrayLists are part of Java’s larger Collections Framework, which we’ll continue to reference throughout this course. 23 videos5 readings2 assignments2 app items So far, we’ve been defining variables as instance variables in our Java classes. Instance variables are just variables defined inside a class, and every instance of a class can have a different value for an instance variable.
In this module, we’ll look at defining static variables in our Java classes. Static variables are also defined as variables inside a class, but with the keyword 'static'. Static variables have the same value for every instance of a class. In fact, you don’t even need to create an instance of a class to use a static variable!
We’ll also look at static methods. And just like static variables, you don’t need to create an instance of a class to use, or call, a static method. In this module, we’re also going to introduce polymorphism, which refers to overloading and overriding. We’ll focus on overloading, which is having two or more methods in the same class, with the same name. 21 videos2 readings2 assignments1 app item
|
3 modules
|
Beginner level
| null |
https://www.coursera.org/learn/java-object-oriented-programming
|
93%
|
985 |
Computational Thinking for K-12 Educators: Variables and Nested Loops
|
Enrollment number not found
|
Rating not found
| null |
Beth Simon
|
University of California San Diego
|
['Sports', 'want', 'Brainstorming', 'Broadcast']
|
How can students learn about abstraction by creating a movie scene? Or make an interactive map using lists? You'll learn (and do it yourself) in this course! This class teaches the concepts of abstraction (methods and parameters) and lists. For each concept, we'll start by helping you connect real-world experiences you are already familiar with to the programming concept you are about to learn. Next, through a cognitively scaffolded process we'll engage you in developing your fluency with problem solving with abstraction and lists in a way that keeps frustration at a minimum.
Along the way you will learn about the common challenges or "bugs" students have with these concepts as well as ways to help them find and fix those concepts. You'll also be guided in running classroom discussions to help students develop deeper understanding of these concepts.
Finally, you'll learn about the importance and logistics of assigning creative, student-designed programming projects.
Additionally, you will create a personal plan for increasing your skills in supporting a culturally responsive learning environment in your classroom. Meet Dr. Simon and fellow learners in this class! Find out what you’ll be doing and learning. 2 videos2 readings1 discussion prompt How can we simplify instructions further with repeats? How do you dance the chicken dance? We’ll cover these questions and more in this module! Learn how nested repeats work by making dance instructions, solving programming puzzles, and creating a program. Prepare for class discussions around challenging questions about nested repeats. 6 videos4 readings2 assignments1 app item1 discussion prompt Be prepared for teaching nested repeats with code.org’s Bee and Zombie programming challenges, and get ready to learn about events! Find out how to grab your students’ attention with events, and practice your understanding by imagining: what if you could control someone with a game controller? Learn more about events by playing with programming puzzles and creating your own program. 2 videos6 readings3 assignments3 discussion prompts In this module, we’ll explore how events are taught in the classroom and go through another code.org challenge: this time, we’re creating the game of Bounce (or Pong), which is just like air hockey! We’ll also introduce how variables are placeholders for data by displaying them as a real-world placeholders: envelopes. Work on getting comfortable with variables in a variety of programming puzzles. 3 videos7 readings3 assignments1 discussion prompt After working through some tricky examples of changing variables, we’re ready to bring variables to your classroom! First, we’ll cover a more thorough lesson plan for the “variables as envelopes” metaphor. Then, we’ll head back to the code.org Artist environment to show the true power of variables and how much they can affect our drawings! 1 video3 readings2 assignments1 app item1 discussion prompt We take a break from programming concepts to ensure that your classroom environment encourages a healthy learning environment. Learn how to make fun assignments a little more approachable by using Parsons’ problems, and explore how you can make your computer lab a respectful and supportive environment for all, especially students that might be underrepresented. 4 videos3 readings1 assignment1 app item1 discussion prompt
|
6 modules
|
Beginner level
|
15 hours to complete (3 weeks at 5 hours a week)
|
https://www.coursera.org/learn/block-programming-k12-educators-variables-nested-loops
| null |
986 |
Toxicology 21: Scientific Applications
|
10,888
|
4.6
| 82 |
Lena Smirnova
|
Johns Hopkins University
|
[]
|
This course familiarizes students with the novel concepts being used to revamp regulatory toxicology in response to a breakthrough National Research Council Report “Toxicity Testing in the 21st Century: A Vision and a Strategy.” We present the latest developments in the field of toxicology—the shift from animal testing toward human relevant, high content, high-throughput integrative testing strategies. Active programs from EPA, NIH, and the global scientific community illustrate the dynamics of safety sciences. This model will give you a broad introduction to the Toxicology 21st century (Tox21c) field and familiarize you with the main document, which summarize the main ideas and principles of Tox21c. 10 videos3 readings1 assignment1 discussion prompt This module will discuss how ToxCast and Tox21 technologies can be used in practice. The US EPA Endocrine Disruptor Screening Program will be discussed in detail and we will demonstrate how the ToxCast platform replaced in vivo tiered approaches in EDSP and, thus, acelerate the process of . In the second lesson of this module, the development of in silico models for toxicity testing will be discussed. 10 videos4 readings1 assignment1 peer review2 discussion prompts This module will familiarize you with the Human Toxome Project run by Johns Hopkins University in collaboration with several university, industry, and research agencies. Omics technologies, their advantages and disadvantages, as well as concepts of Adverse Outcome Pathways (AOP) and Pathways of Toxicity (PoT) will be discussed. 10 videos2 readings1 assignment1 discussion prompt The first lesson in this module will explain the concept of read-across, why it is important for regulatory risk assessment, and how it can be implemented by industry in response to REACH legislation. The organotypic cultures lesson will teach you about existing in vitro cell-based models starting from simple monolayer cultures of cell lines and ending with complex combined organ-on-a-chip and human-on-a-chip approaches. 18 videos3 readings2 assignments1 discussion prompt This module will teach you the role of miRNA and epigenetics in toxicology and environmental health. 6 videos1 reading1 assignment1 discussion prompt In this module you will learn about important component of in vitro toxicology such as in vitro to in vivo extrapolation (IVIVE) and physiologically based biokinetic modeling. You will learn why it is important to consider biokinetics in vitro and see some example of biokinetics modeling in vitro. This lesson will also give you a biometry prospective of in vitro toxicology. You will learn which methods can be used to analyze big data. 8 videos3 readings1 assignment1 peer review In this lesson you will learn about integrated testing strategies and how they differ from individual tests or test batteries. Also a wrap-up lesson "beyond chemical" will summaries your knowledge from this course and give a out-look for further directions in the field of alternatives to animal testing. 11 videos2 readings2 assignments
|
7 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/toxicology-21
|
97%
|
987 |
Microsoft Copilot for Software Development Specialization
|
Enrollment number not found
|
Rating not found
| null |
Microsoft
|
Microsoft
|
['Document Generation', 'VS Code', 'Project Management', 'AI Tools in Business', 'GenAI Basics', 'GitHub Copilot', 'vs code', 'Developing with AI', 'GenAI', 'Code Generation', 'Code Analysis', 'Ethics in AI', 'Document Generation', 'VS Code', 'Project Management', 'AI Tools in Business', 'GenAI Basics', 'GitHub Copilot', 'vs code', 'Developing with AI', 'GenAI', 'Code Generation', 'Code Analysis', 'Ethics in AI']
|
Are you ready to explore the cutting-edge world of generative AI? Take your coding practices to the next level with this program and learn how generative AI tools, particularly GitHub Copilot, can transform your development workflow and boost your productivity. From understanding the basics of generative AI to learning how to apply it in code review, documentation, development planning, and more, you will learn practical skills based on real-life scenarios to help you enhance your abilities. This program, curated and presented by industry experts, will show you how to integrate generative AI into practical scenarios. The flexible, self-paced learning schedule accommodates your personal and professional commitments, focusing on practical applications and hands-on projects and nurturing your skills without the demands of academic report writing. By completing this program, you will: Gain valuable skills in generative AI Enhance your existing abilities Add new techniques to your toolkit Understand how to integrate generative AI into your development workflows Boost your productivity and effectiveness No prerequisites required.Whether you're a seasoned developer or just starting out, this course will equip you with the skills to harness the power of AI and boost your productivity. Unlock your full potential with Copilot. Enroll today! Applied Learning Project Learners will gain practical experience using Microsoft Copilot Chat for code completion, Flask-based to-do app for code testing and GitHub Copilot to translate code snippets. These hands-on activity offers experiential learning opportunities, enabling learners to apply AI tools in real coding scenarios, managing projects effectively and applying Copilot's analytical capabilities in your everyday coding tasks. This course introduces developers to generative AI technologies, focusing on their practical applications in software development. You will explore the core concepts of generative AI and understand the basic functionalities and ethical considerations of generative AI. The course is structured to provide a comprehensive overview, starting with the fundamentals of generative AI and progressing to its practical uses in code review, documentation, and project planning. Through engaging modules, you will gain a solid foundation in navigating the risks and responsibilities associated with AI. Hands-on activities and quizzes will reinforce the knowledge gained, ensuring that you are well-equipped to harness the potential of generative AI in your development workflows. This module is designed to equip you with the essential skills to set up and optimize your environment for using GitHub Copilot effectively. You will gain practical knowledge on installing and configuring Visual Studio Code (VS Code) across different operating systems, including Mac, PC, and Linux. This course covers the basics of generating code suggestions with GitHub Copilot, from setting up the extension to exploring its chat capabilities. Additionally, you will refine your prompt crafting skills, applying techniques like zero-shot, one-shot, and few-shot learning to enhance the quality of Copilot’s suggestions. The course also delves into advanced features and best practices, guiding you through creating practical projects, such as a Todo application in Python and customizing Copilot to fit your development needs. Through hands-on activities, quizzes, and comprehensive lessons, you will be well-prepared to harness the full potential of GitHub Copilot in your software development workflows. This course provides a comprehensive guide to using GitHub Copilot within the Visual Studio Code environment, focusing on practical and advanced applications. The course covers building a simple Pomodoro timer, including setting up the Next.js environment, designing the timer interface, and implementing core functionality, as well as improving the timer by refactoring for efficiency, adding tests, and exploring case studies. The course also focuses on practical coding applications, such as code translation and debugging, through hands-on activities. Throughout the course, you will engage in practical projects, quizzes, and hands-on activities to master the use of GitHub Copilot, making it ideal for developers looking to enhance their coding efficiency and explore the full potential of AI-assisted development. This course explores the potential of GitHub Copilot in project management, focusing on AI-driven code review, comprehensive documentation, and meticulous development planning. You will learn to optimize code, identify inefficiencies, generate test cases, and apply best practices for code review using GitHub Copilot. The course also covers generating and managing documentation with Copilot, including version control and best practices. Additionally, it focuses on planning development strategies, ideating with AI, and implementing plans effectively. Hands-on activities, practice quizzes, and module quizzes ensure practical understanding and mastery of each topic.
|
4 course series
|
Intermediate level
|
1 month (at 5 hours a week)
|
https://www.coursera.org/specializations/microsoft-copilot-for-software-development
| null |
988 |
Migration and health
|
Enrollment number not found
|
Rating not found
| null |
Christina Atchison
|
Imperial College London
|
['global', 'right to health', 'Evaluation', 'Human Migration', 'health system']
|
Migration and health is the second instalment of the wider Global Health Challenges and Governance specialisation from Imperial College London's Global Master of Public Health (GMPH). The scope and content of this course has been developed from the ground up by a combined team of academics and practitioners drawing on a wealth of real-world public health experience as well as deep academic knowledge. Through short video lectures, readings and a wide range of interactive activities, learners will be immersed in the intersection of migration and health. Designed for those new to the discipline, over four modules (intended for one week of learning each), learners will become familiar with the relationship between migration and health. Learners will be introduced to key terms and global trends in migrations, the profound impact of crises in non-health sectors on health, and policy instruments addressing migration. By the end of this course, learners will be able to describe international treaties protecting migrants’ right to health and migrant sensitive health systems. Learners will also be able to critically evaluate whether and how their national health system is providing universal health coverage to migrants.
The subsequent course in this specialisation requires the knowledge from this course, as learners will take a deep dive into climate change by applying their global health analytical skills and knowledge of multilateral policy instruments to this important global health challenge. 7 readings1 discussion prompt1 plugin This module begins by exploring how policies, and global trends and crises in non-health sectors can have a profound impact on health. More and more, health is the unwitting victim of global trends and crises, beyond our direct control, and policies made in the international systems that tie countries, economies, commerce, and trade together. We introduce learners to key terms and global trends in migration, and examine global governance structures and key policy instruments addressing migration. 2 videos10 readings1 assignment4 discussion prompts This module introduces learners to the different stages of migration, and health-related risks and opportunities at each stage. We then explore health risks and opportunities at each stage of migration in different settings, and for a specific vulnerable group of migrants, those people who are trafficked. 2 videos6 readings4 discussion prompts This module introduces learners to migrant health global governance structures. Having previously considered the different stages of migration, we now look at the health-related policy processes and perspectives in relation to migrants. Historically, measures around migrant health operated primarily to protect the public health of the native population from the ‘threat’ posed by immigrants and travelers. We examine how, over time, there has been growing recognition that international policy-level attention to the health and human rights of migrants is required, with several international treaties now including provisions to protect migrants’ rights to health. 2 videos4 readings3 discussion prompts This module introduces the learner to the concept of a migrant sensitive health system. We then explore how a number of different national health systems across the world are providing healthcare to migrants. Learners are introduced to the WHO Universal Health Coverage cube before having the opportunity to use the framework to examine how their national health system is providing universal health coverage to migrants. 2 videos3 readings1 assignment1 peer review2 discussion prompts4 plugins
|
5 modules
|
Beginner level
|
31 hours to complete (3 weeks at 10 hours a week)
|
https://www.coursera.org/learn/migration-health
| null |
989 |
Microsoft Public Relations and Communications Associate Professional Certificate
|
2,236
|
4.6
| 20 |
Microsoft
|
Microsoft
|
['Proofreading', 'Integrated Marketing Communications', 'Integrated PR Campaigns', 'Marketing Communications', 'Public Relations', 'Generative AI', 'Content Management', 'Content Development', 'Communications']
|
Are you ready to launch a dynamic career in Public Relations and Communications? This Professional Certificate Program is your gateway to the exciting world of PR, designed specifically for aspiring professionals eager to make a mark in the industry. This comprehensive program brought to you by Microsoft, comprising five courses, equips you with the essential skills and knowledge to excel in various PR roles such as PR Associate, Communications Coordinator, and Media Relations Coordinator. You'll master the basics of Public Relations, strategic planning, and media relations while exploring the impact of Generative AI. Become proficient in content development and management, leveraging AI tools to enhance your creative process. Learn to handle crises with effective communication strategies, build strong media relationships, and integrate PR with marketing for cohesive campaigns. You'll learn how to use metrics to evaluate PR campaigns and craft comprehensive communication strategies. You will also discover how to conduct a comprehensive stakeholder analysis to identify and characterize different stakeholder groups involved in a PR campaign. Along the way, you will explore how to incorporate Microsoft’s tools, such as Copilot into your future work. This program not only provides theoretical knowledge but also hands-on experience, preparing you for the real-world challenges of Public Relations. Enroll now and take the first step towards becoming a PR powerhouse! Applied Learning Project Throughout the program, you’ll get to practice your new public relations and communications skills through hands-on projects including: Developing basic PR strategies Creating and managing content for a PR campaign Formulating a crisis management communication plan Designing an integrated PR and marketing campaign Establishing a comprehensive stakeholder relations and reporting strategy By the end, you’ll have a professional portfolio that you can show to prospective employers. Describe public relations and it's role and importance across various organization types Identify and evaluate essential components of public relations campaign strategy Explain core media relations principles including how to craft a media pitch Distinguish different types of PR content based on their purpose and function within a PR campaign Apply editing and proofreading best practices to ensure the quality and effectiveness of PR content Develop strategies for organizing and managing various types of PR content efficiently Effectively plan and schedule PR campaign content for optimal impact using a content calendar that is aligned with a PR strategy The core principles and strategies for effective crisis communication for different types of crises How to initiate and maintain beneficial relationships with various media outlets and how to leverage those relationships in times of crisis How to develop a crisis communication plan that integrates media relations and AI capabilities for both internal and external communication Develop strategies for integrating multiple communication channels to deliver a cohesive and effective campaign Craft compelling PR messages with powerful storytelling and tailor these messages to various PR scenarios Enhance the effectiveness of communication and storytelling strategies with AI tools Create a comprehensive blueprint for effective integrated campaigns while streamlining your PR processes Conduct a stakeholder analysis to identify key stakeholders and their potential impact and influence in various PR scenarios Analyze key metrics to assemble basic reports that summarize PR campaign results Develop a strategic plan for communication with community and government stakeholders that integrates their specific concerns Implement strategies for stakeholder engagement and the integration of their feedback through a PR campaign
|
5 course series
|
Beginner level
|
5 months (at 6 hours a week)
|
https://www.coursera.org/professional-certificates/microsoft-public-relations
| null |
990 |
The Age of Sustainable Development
|
139,538
|
4.7
| 3,737 |
Jeffrey Sachs
|
Columbia University
|
['Energy', 'Sustainable Energy', 'Urban Planning', 'Environmental Protection']
|
The Age of Sustainable Development" gives students an understanding of the key challenges and pathways to sustainable development - that is, economic development that is also socially inclusive and environmentally sustainable. Information about the general course structure and reading list can be found here. 3 readings Professor Sachs provides an overview of the challenges the world faces, and introduces the topic of sustainable development. 5 videos1 assignment Professor Sachs delves into the reasons for and the measurements of inequality between and within countries. 5 videos1 assignment Professor Sachs provides a history of economic development, starting with the Industrial Revolution and ending with the current state of modern economic growth. 5 videos1 assignment Professor Sachs analyzes the intersecting roles of various factors that contribute to some countries advancing while others do not. 5 videos1 assignment Professor Sachs outlines the pathways for achieving the end of extreme poverty. 5 videos1 assignment Professor Sachs details the various planetary boundaries and their implications for growth dynamics. 5 videos1 assignment Professor Sachs delves into the ethics of wealth, poverty and inequality as well as the forces that widen inequalities. 5 videos1 assignment Professor Sachs provides an overview of the state of modern education, and what needs to be achieved for sustainable development. 5 videos1 assignment Professor Sachs provides an overview of the challenges and pathways to achieving universal health coverage. 5 videos1 assignment Professor Sachs provides an overview of food security, farm systems, and ecology and reviews what can be done to achieve a sustainable global food supply. 5 videos1 assignment Professor Sachs looks into what makes a city sustainable, the patterns of urbanization, and pathways for urban resilience around the world. 5 videos1 assignment Professor Sachs provides an introduction to the science behind climate change, and describes the negotiations and policies that are necessary to mitigate and prevent the consequences. 5 videos1 assignment Professor Sachs reviews the various threats to the world's ecosystem and biodiversity. 5 videos1 assignment Professor Sachs recounts the history of the Sustainable Development Goals (SDGs), and describes what is necessary to achieve them. 5 videos2 assignments
|
15 modules
| null |
29 hours to complete (3 weeks at 9 hours a week)
|
https://www.coursera.org/learn/sustainable-development
|
96%
|
991 |
Data Integration with Microsoft Azure Data Factory
|
17,527
|
3.8
| 163 |
Microsoft
|
Microsoft
|
['Microsoft Azure', 'Data Integration', 'Data Pipelines']
|
In this course, you will learn how to create and manage data pipelines in the cloud using Azure Data Factory. This course is part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services. It is ideal for anyone interested in preparing for the DP-203: Data Engineering on Microsoft Azure exam (beta).
This is the third course in a program of 10 courses to help prepare you to take the exam so that you can have expertise in designing and implementing data solutions that use Microsoft Azure data services. The Data Engineering on Microsoft Azure exam is an opportunity to prove knowledge expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions that use Microsoft Azure data services. Each course teaches you the concepts and skills that are measured by the exam.
By the end of this Specialization, you will be ready to take and sign-up for the Exam DP-203: Data Engineering on Microsoft Azure (beta). Describe the core components of Azure Data Factory that enable you to create large scale data ingestion solutions in the cloud 9 videos7 readings3 assignments1 discussion prompt1 plugin Describe the various methods that can be used to ingest data between various data stores using Azure Data Factory 5 videos4 readings2 assignments Perform common data transformation and cleansing activities within Azure Data Factory without using code Implement Slowly Changing Dimension using Azure Data Factory or Azure Synapse Pipelines 7 videos7 readings5 assignments1 plugin Use Azure Data Factory to orchestrate large scale data movement by using other Azure Data Platform and Machine Learning technologies 6 videos1 reading3 assignments Integrate SQL Server Integration Services packages into an Azure Data Factory solution 3 videos3 readings2 assignments Publish your Azure Data Factory work between different environments 3 videos6 readings2 assignments Ingest data from Azure Data Share into Azure Data Factory pipelines to build automated ingestion pipelines 6 videos6 readings7 assignments Practice Exam on Data integration at scale with Azure Data Factory or Azure Synapse Pipeline 2 videos2 readings1 assignment1 discussion prompt
|
8 modules
|
Intermediate level
|
15 hours to complete (3 weeks at 5 hours a week)
|
https://www.coursera.org/learn/azure-data-factory-data-integration
| null |
992 |
Healthy Practices: Nutrition, Physical Activity, and Community and Family Participation
|
25,544
|
4.7
| 826 |
Daniel Nicklas
|
University of Colorado System
|
[]
|
In this course you will find a comprehensive overlook of healthy practices in public schools in the USA, including: physical activity and nutrition in the school setting. We will review the basics of some of the regulatory programs found in the United States that support healthy students through nutrition education and nutrition programs. You will be able to explain some of the nutritional components such as, alternatives to the use of Sugar-Sweetened Beverages. Many of these principles can be applied to students in schools throughout the globe. You will understand how the schools can support physical activity throughout the day and how they can effectively offer physical education. Learners will be able to explain MVPA, or moderate to vigorous physical activity. They will identify this as the newest method for measuring and evaluating what counts as physical activity in terms of METs. Participants in the course will be able to explain the science behind the recommended "60 minutes of Physical Activity" and what counts toward MVPA both during and outside of the school day.
Learners will be able to evaluate and explain how what students eat and how they exercise impacts student success. We will provide you with information to help you to promote the teamwork that it takes to implement successful nutritional and physical activity programs. Our discussion will include where to find and how to develop community support and encourage family participation.
Later in the course you will understand how attendance impacts student success. Together we will look at real-life examples of programs in a school setting and this will help you to recognize what impact you can have on improving the health and success of students in your own community. In the following module you will learn more about school nutrition. We’ll start by better understanding the differences between nutrition and nutrition services before we learn more about nutrition standards and the historical and scientific reasoning behind them. We’ll end the module with practical ways that you can promote a positive nutritional environment in your school. 5 videos5 readings1 assignment In this module you will learn about physical activity in and out of school and about the physical, mental, and social benefits of physical activity. We’ll learn more about the differences in terminology and the science behind physical activity and how it relates to children’s overall health. As you’ll see in this module, physical activity is one of the greatest preventative measures regarding health problems later in life so, accordingly, we’ll learn more about how we can craft plans to encourage and support physical activity in and out of the classroom. 4 videos1 reading1 assignment In this module we will learn about what communities can do to help create healthy environments in schools. We’ll specifically look at how three components of the community (individuals, businesses, and families) can be utilized to support children’s health. We’ll also discuss important facts regarding school attendance. 5 videos3 readings1 assignment In this module, we’ll learn more about programs that benefit children when class is not in session. We’ll learn more about the impact of health programs offered in partnership with local businesses and how they can benefit children’s health outside of the traditional classroom setting. 4 videos4 readings1 assignment
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/healthy-practices-nutrition-physical-activity-community-family-participation
|
99%
|
993 |
Advanced Portfolio Construction and Analysis with Python
|
22,932
|
4.7
| 498 |
Claudia Carrone
|
EDHEC Business School
|
[]
|
The practice of investment management has been transformed in recent years by computational methods. Instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language. In this course, we cover the estimation, of risk and return parameters for meaningful portfolio decisions, and also introduce a variety of state-of-the-art portfolio construction techniques that have proven popular in investment management and portfolio construction due to their enhanced robustness. As we cover the theory and math in lecture videos, we'll also implement the concepts in Python, and you'll be able to code along with us so that you have a deep and practical understanding of how those methods work. By the time you are done, not only will you have a foundational understanding of modern computational methods in investment management, you'll have practical mastery in the implementation of those methods. If you follow along and implement all the lab exercises, you will complete the course with a powerful toolkit that you will be able to use to perform your own analysis and build your own implementations and perhaps even use your newly acquired knowledge to improve on current methods. 9 videos3 readings1 assignment1 discussion prompt1 ungraded lab 7 videos1 reading1 assignment1 discussion prompt 7 videos3 readings1 assignment1 discussion prompt 7 videos4 readings1 assignment1 discussion prompt
|
4 modules
|
Intermediate level
|
12 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/advanced-portfolio-construction-python
| null |
994 |
Business Data Management and Communication Specialization
|
3,399
|
4.9
| 58 |
Unnati Narang
|
University of Illinois Urbana-Champaign
|
['Financial Accounting', 'Data Analysis', 'Business Analytics', 'Asset Management', 'Rstudio', 'Financial Accounting', 'Data Analysis', 'Business Analytics', 'Asset Management', 'Rstudio']
|
In a world driven by big data, it is crucial to understand how valuable information can be extracted from large volumes of data. Further, it is pivotal to utilize information to its full potential. This not only requires one to extract value from data but also to effectively communicate the information obtained. The Business Data Management and Communication Specialization is tailored to deliver a well-balanced curriculum that focuses on all three aspects - Understanding Data, Extracting Valuable Information, and Effective Communication. The courses in this Specialization will focus on advanced accounting, working with big data, communicating data and information analysis. Topics covered include: Understand the basics of how to analyze balance sheet and cash flow statements Understand how accrual accounting and fundamental accounting concepts work Learn how to collect, analyze, and visualize data and use the same in decision making processes Learn how to use R to communicate data analytics results Explore various ways that information can generate economic value Understand how crucial information is and learn how to gauge the potential of valuable information Applied Learning Project The core concept based on which the specialization is structured is that data and information, when utilized effectively, can provide significant economic benefits. Getting from raw data to valuable information involves a plethora of analytical processes and understanding of the underlying data. Each course in the specialization will provide an in-depth application and data analysis exercise. Accounting information and how it is used by different capital market participants Record financial information and produce the main financial statements Fundamental accounting concepts and revenue recognition criteria in preparing financial statements, Conduct the accounting for short-term assets, with a particular focus on accounts receivables and inventories. to account for fixed assets understand accounting for liabilities evaluate shareholders’ equity section of a balance sheet, and understand preparation and information provided by cash flows statement. This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients. You will learn how to process data using R and RStudio. You will also explore the interaction between business principles and data analytics. Appreciate the unique economic, accounting, and legal characteristics of information. Understand and apply methods for conceiving and generating broad-based and transformative business benefits from available information assets. Identify and adapt traditional asset management principles and practices toward the improved management of information assets. Measure information’s various value characteristics to help justify or prove information-related expenditures. Identify and adapt traditional asset management principles and practices toward the improved management of information assets. Measure information’s various value characteristics to help justify or prove information-related expenditures. Articulate the challenges, pitfalls, and paradoxes regarding information’s role as a something owned and controlled. Lay out new and emerging organizational roles for treating information as an actual business asset.
|
6 course series
|
Intermediate level
|
2 months (at 10 hours a week)
|
https://www.coursera.org/specializations/business-data-management-communication
| null |
995 |
Introduction to Data Analytics for Business
|
180,991
|
4.7
| 3,131 |
David Torgerson
|
University of Colorado Boulder
|
['Data Model', 'Data Quality', 'Data Analysis', 'SQL']
|
This course will expose you to the data analytics practices executed in the business world. We will explore such key areas as the analytical process, how data is created, stored, accessed, and how the organization works with data and creates the environment in which analytics can flourish. What you learn in this course will give you a strong foundation in all the areas that support analytics and will help you to better position yourself for success within your organization. You’ll develop skills and a perspective that will make you more productive faster and allow you to become a valuable asset to your organization.
This course also provides a basis for going deeper into advanced investigative and computational methods, which you have an opportunity to explore in future courses of the Data Analytics for Business specialization. Welcome to week 1! In this module we’ll learn how to think about analytical problems and examine the process by which data enables analysis & decision making. We’ll introduce a framework called the Information-Action Value chain which describes the path from events in the world to business action, and we’ll look at some of the source systems that are used to capture data. At the end of this course you will be able to: Explain the information lifecycle from events in the real world to business actions, and how to think about analytical problems in that context , Recognize the types of events and characteristics that are often used in business analytics, and explain how the data is captured by source systems and stored using both traditional and emergent technologies, Gain a high-level familiarity with relational databases and learn how to use a simple but powerful language called SQL to extract analytical data sets of interest, Appreciate the spectrum of roles involved in the data lifecycle, and gain exposure to the various ways that organizations structure analytical functions, Summarize some of the key ideas around data quality, data governance, and data privacy 9 videos3 readings1 assignment2 discussion prompts In this module we’ll learn about the technologies that enable analytical work. We’ll examine data storage and databases, including the relational database. We’ll talk about Big Data and Cloud technologies and ideas like federation, virtualization, and in-memory computing. We’ll also walk through a landscape of some of the more common tool classes and learn how these tools support common analytical tasks. 7 videos3 readings1 assignment2 discussion prompts In this module we’ll learn how to extract data from a relational database using Structured Query Language, or SQL. We’ll cover all the basic SQL commands and learn how to combine and stack data from different tables. We’ll also learn how to expand the power of our queries using operators and handle additional complexity using subqueries. 7 videos3 readings1 assignment1 discussion prompt In this module we focus on the people and organizations that work with data and actually execute analytics. We’ll discuss who does what and see how organizational structures can influence efficiency and effectiveness. We’ll also look at the supporting rules & processes that help an analytical organization run smoothly, like Data Governance, Data Privacy, and Data Quality. 6 videos2 readings1 assignment1 peer review2 discussion prompts
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/data-analytics-business
|
95%
|
996 |
Construction Practices in Metro Rails
|
Enrollment number not found
|
Rating not found
| null |
Subject Matter Expert
|
L&T EduTech
|
['Proficiency in the concepts of TOD and Feasibility studies for Metro projects', 'Apply suitable construction practices for elevated and underground Metros']
|
This course offers a comprehensive exploration of Mass Rapid Transit Systems (MRTS) through essential modules. Beginning with an "Introduction to MRTS," it establishes foundational principles for metro planning. The "Transit-Oriented Development (TOD)" module delves into the critical relationship between metro systems and urban development, enriched with case studies. The "Feasibility Studies" module equips participants with tools for assessing project viability. "Planning and Integration of Metro Systems" addresses challenges and strategies for coordinating various configurations. The course covers metro station planning, MEP systems imparting practical knowledge for successful metro projects and contribute to sustainable urban development and efficient public transportation. Target Learners:
• Undergraduate students of Civil Engineering
• Post-Graduate Students of Transportation and Geotechnical Engineering
• Practicing Civil, Transportation and Geotechnical Engineers
Prerequisites:
• Geotechnical Engineering
• Fundamentals on Structural Analysis
• Basics on RCC Design The "Introduction to Planning of Metros" module offers a thorough exploration of crucial urban transportation topics, including MRTS, Transit-Oriented Development, feasibility studies, sustainable and smart technologies, and the historical evolution of metros. This comprehensive overview equips learners with a holistic understanding of modern urban transit challenges and solutions. Focusing on essential principles for interface design, the module emphasizes urban planning intricacies, constraints, and restrictions. It delves into the seamless integration of diverse metro systems, incorporating insights on Building Information Modeling (BIM) for comprehensive planning. Learners gain valuable perspectives on optimizing metro functionality amidst urban challenges and technological advancements, fostering a well-rounded comprehension of metro planning. 13 videos1 assignment The "Overview of Elevated Metros" module provides a comprehensive exploration of key topics essential for understanding elevated metro systems. It covers alignment and span configuration, elucidating the principles guiding the layout of elevated metro viaducts. The module delves into the components of elevated metro viaducts, elevated stations, and crucial considerations in choosing the type of pier and bearing systems. It explores various superstructure types, emphasizing the Balanced Cantilever method. Detailed insights are provided on station overall layout and the loads impacting stations. This module equips learners with a well-rounded understanding of the intricacies involved in planning and constructing elevated metros. 12 videos1 assignment The "Construction of Elevated Metros" module provides a comprehensive exploration of crucial topics essential for executing elevated metro projects. It begins by addressing soil conditions and foundation types, guiding learners in selecting appropriate substructure systems. The module then delves into precast mould development, offering insights into formwork systems overview and design. Precast erection methods and launching techniques are thoroughly examined, providing practical knowledge for constructing elevated metro viaducts. The module concludes by exploring obligatory span construction, ensuring participants gain a holistic understanding of the construction processes involved in executing elevated metro projects, from foundation considerations to advanced precast construction methods. 15 videos1 assignment The "Construction of Underground Metros" module provides a comprehensive exploration of critical topics essential for executing underground metro projects. It begins by examining earth retaining systems, encompassing secant pile walls, contiguous pile walls, soldier piles, and diaphragm walls, offering insights into selecting appropriate retaining methods for varied soil conditions. The module then delves into tunnel construction methods, including cut and cover, drill and blast, and bored methods like NATM (New Austrian Tunneling Method) and NMT (Non-Traditional Tunneling). Learners gain practical knowledge in constructing underground metros, covering a spectrum from earth retaining structures to diverse tunneling techniques, ensuring a well-rounded understanding of underground metro construction complexities. 11 videos1 assignment This module offers a comprehensive overview of critical components in metro systems. It covers HVAC systems, Tunnel ventilation systems, Public health engineering aspects, electric systems, Fire safety, alarms, prevention, and emergency response. Overall, the module provides a thorough understanding of the intricate systems and safety measures integral to the efficient functioning and well-being of metro systems. 7 videos1 assignment This module, addressing the Emerging Trends in Metro Systems, it explores futuristic technologies in transportation infrastructure, including Maglevs, Vactarian trains, Hyperloop, and the advent of flying taxis. 7 videos1 assignment
|
6 modules
|
Intermediate level
|
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/construction-practices-in-metro-rails
| null |
997 |
Emergency Care: Pregnancy, Infants, and Children
|
24,040
|
4.8
| 299 |
Arthur Pliaconis
|
University of Colorado System
|
['infant', 'ingestion', 'listening', 'emergency']
|
Welcome to the final course of lectures in your quest to master EMT basics. In this course, we will cover some of the highest-stress patient populations: pregnant patients and kids, also known as pediatrics. To wrap up your EMT knowledge we will end this course with information about hazmat situations, extricating patients from tight spots and finally how you write a note about your patient care. You will learn to ensure it communicates what your assessment of the patient was, what interventions you performed and why you did them. You will build on your knowledge of anatomy, patient assessment and scene safety to develop an approach to these new patient populations. We will walk through the things that make pregnant patients and pediatric patients different but also what makes them the same as all the patients you care for.
Prepare yourself for some noisy kids, some uncomfortable moms and hopefully a lot of fun learning new things. In the next few lessons, you will learn about some basics of pregnancy as well as the care of the pregnant patient all the way through delivery of a baby. While it might seem crazy, part of your scope of practice is an emergency delivery! 9 videos6 readings2 assignments Next up is learning how to manage the newly born baby. Depending on the gestational age, the prenatal care and the delivery, the newborn can present in a variety of ways. You will learn a progression of interventions to help with your care of newborns. After learning about how to assess and manage the newborn, we will move on to the wide and wild world of kids, along with some tips and tricks for getting the info you need without all the tears. 12 videos4 readings1 assignment In this module, we are going to cover some pediatric specific problems that affect the different body systems. We will focus on diseases that are mostly found in the pediatric population and will refer you back to prior lessons to refresh on those things that affect all populations. We will also review in more detail some of the anatomic and developmental changes that occur during childhood that can impact your care for certain conditions. 18 videos6 readings1 assignment We’ll be finishing off the course with a few more crucial skills and concepts to round out your EMT education. These are the odds and ends that bring everything together. 12 videos3 readings1 assignment
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/emergency-care-pregnancy-infants-children
|
98%
|
998 |
Learn to code with AI
|
14,136
|
4.7
| 79 |
Per Harald Borgen
|
Scrimba
|
['Computer Programming', 'HTML', 'Machine Learning', 'JavaScript', 'Cascading Style Sheets (CSS)']
|
Imagine waking up tomorrow as a web developer. What would you want to build? With AI tools like ChatGPT, you're already a developer, regardless of your experience, if you know how to work with them.
So in this course, you'll build functional, interactive front-end projects while learning how to write effective prompts and debug and refine your code with the help of AI.
No coding experience needed! We'll focus on helping you prototype and build projects with AI's assistance, turning you from a non-coder into a capable problem solver.
By the end of this course, you'll have a collection of mini-projects, newly acquired skills, and a solid foundation to keep building with AI.
You'll work on various projects using HTML, CSS, and JavaScript. Let's do this! Learn to build UI components, web pages, web apps, and even a musical instrument using HTML, CSS, and JavaScript! All with the help of AI. 16 plugins Take your project-building skills to the next level. You'll learn to build a game, a Chrome extension and even a mobile app! 1 assignment14 plugins Learn practical skills in using Firebase to build and deploy interactive, database-driven applications efficiently. 10 plugins
|
3 modules
|
Beginner level
|
4 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/learn-to-code-with-ai
| null |
999 |
Using clinical health data for better healthcare
|
13,218
|
4.7
| 112 |
Tim Shaw
|
The University of Sydney
|
[]
|
Digital health is rapidly being realised as the future of healthcare. While this is placing emphasis on the input of quality health data in digital records and systems, the delivery of safe and quality healthcare relies not only on the input of data, but also the ability to access and derive meaning from data to generate evidence, inform decision making and drive better health outcomes. This course provides insight into the use of healthcare data, including an overview of best practices and the practical realities of obtaining useful information from digital health systems via the understanding of the fundamental concepts of health data analytics.
Learners will understand why data quality is essential in modern healthcare, as they are guided through various stages of the data life cycle, starting with the generation of quality health data, through to discovering patterns and extracting knowledge from health data using common methodologies and tools in the basic analysis, visualisation and communication of health data. In doing so, learners explore current healthcare delivery contexts, and future and emerging digital health data systems and applications that are rapidly becoming tomorrow’s reality.
On completion of this course, you will be able to:
1. Identify digital health technologies, health data sources, and the evolving roles of health workforce in digital health environments
2. Understand key health data concepts and terminology, including the significance of data integrity and stakeholder roles in the data life cycle
3. Use health data and basic data analysis to inform and improve decision making and practice.
4. Apply effective methods of communication of health data to facilitate safe and quality care.
During this course, you will interact with learning content contributed by:
• Digital Health Cooperative Research Centre
• Australian Digital Health Agency
• eHealth NSW
• Sydney Local Health District
• The NSW Ministry of Health
• Health Education and Training Institute
• Clinical Excellence Commission
• Chris O’Brien Lifehouse
• Monash Partners / Australian Health Research Alliance
• Australian Research Data Commons
• Justice Health & Forensic Mental Health Network
• South Eastern Sydney Local Health District
• Western Sydney Local Health District
• Westmead Breast Cancer Institute
• Agency for Clinical Innovation
• Western NSW Local Health District
• Sydney Children’s Hospital Network
This course is a collaborative venture between NSW Health, the University of Sydney and the Digital Health Cooperative Research Centre, including dedicated resources from eHealth NSW, Health Education and Training Institute, and the Research in Implementation Science & eHealth group. While many learning resources and case examples are drawn from the NSW Health service context, this course has relevance for all existing and future health workforce, regardless of role or work context.
Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation. This module explores current digital health environments, identifying the many uses of digital health technologies and health data sources. We look at the evolving roles of the health workforce in digital health environments, considering roles and responsibilities. The importance of data analytics for decision making and healthcare outcomes is introduced.
Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation. 7 videos5 readings3 assignments1 discussion prompt In this module, we review key health data concepts and terminology. We emphasise the importance of data integrity and the benefits and consequences of high or low quality data. We look at the data life cycle and the roles and responsibilities of all stakeholders in the provision of quality healthcare. There are some case studies illustrating the consequences of poor quality data and we also look at the fundamentals of digital health legislation and policy. Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation. 8 videos3 readings4 assignments1 discussion prompt In this module, we look at the use of health data and basic data analysis to inform and improve decision making and practice. We explore some common methods and tools used in the analysis of health data. There is an opportunity to develop a data query and to practice working with data. Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation. 8 videos3 readings3 assignments1 peer review In the final module, we look at the various modes of communication appropriate for sharing the results produced by data analysis. We consider how effective communication of digital health data contributes to greater consumer engagement and well-being as well as more effective, evidence-based decision making within the healthcare system. Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation. 9 videos2 readings1 assignment1 discussion prompt
|
4 modules
|
Beginner level
|
15 hours to complete (3 weeks at 5 hours a week)
|
https://www.coursera.org/learn/healthcare-data
| null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.