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700 |
Investment Management with Python and Machine Learning Specialization
|
43,573
|
4.5
| 1,608 |
Sean McOwen
|
EDHEC Business School
|
['Risk Management', 'Portfolio construction and analysis', 'Python programming skills', 'Portfolio Optimization', 'Implementation of data science techniques in investment decisions']
|
Gain an intuitive understanding for the underlying theory behind Modern Portfolio Construction Techniques Write custom Python code to estimate risk and return parameters Utilize powerful Python optimization libraries to build scientifically and systematically diversified portfolios Build custom utilities in Python to test and compare portfolio strategies Analyze style and factor exposures of portfolios Implement robust estimates for the covariance matrix Implement Black-Litterman portfolio construction analysis Implement a variety of robust portfolio construction models Learn the principles of supervised and unsupervised machine learning techniques to financial data sets Understand the basis of logistical regression and ML algorithms for classifying variables into one of two outcomes Utilize powerful Python libraries to implement machine learning algorithms in case studies Learn about factor models and regime switching models and their use in investment management Learn what alternative data is and how it is used in financial market applications. Become immersed in current academic and practitioner state-of-the-art research pertaining to alternative data applications. Perform data analysis of real-world alternative datasets using Python. Gain an understanding and hands-on experience in data analytics, visualization and quantitative modeling applied to alternative data in finance
|
4 course series
|
Beginner level
|
2 months (at 10 hours a week)
|
https://www.coursera.org/specializations/investment-management-python-machine-learning
| null |
701 |
Strategies for winning. Meteorology in a round the world regatta
|
5,681
|
4.5
| 137 |
Tomàs Molina
|
Universitat de Barcelona
|
[]
|
In this course you can learn about the mechanics of global weather, the foundations of ocean meteorology, predictive modeling and how sailors receive data via satellite and use high-performance navigation software. This course looks at oceanic meteorology and climatology through the lens of the sport of sailing.
You will gain a basic knowledge of meteorology needed by sailors to take part in a regatta such as the Barcelona World Race, the only double-handed, round the world regatta with no stops.
You will learn about the strategies employed during a round the world regatta and how these are put to use on board the latest ocean racing yachts. In this module you will learn the foundations for an understanding of general and in particular maritime meteorology. What are the factors and engines powering the weather? What do we need to know to understand the weather phenomena we experience every day? What do ocean sailors need to know to predict the weather? Instructors: Tomàs Molina, Santi Serrat 13 videos13 readings1 assignment In this module you will learn:
How meteorological predictions are made. What numerical weather models and equations look like. This will be explained by Tomàs Molina in Module 2.1
You will look at the forecasting structures that help us to interpret the information given by the models:
Advection, troughs, ridges, barometric swamps and low pressure systems. These will be explained by Tomàs Molina in Module 2.2
What the basic prediction models used by sailors are. This will be explained by Marcel van Triest in Module 2.3
Remember you can access to the help forum
. If you are experiencing difficulty learning or accessing course content, or if you simply want more information. 10 videos12 readings1 assignment In this module you will learn how sailors use meteorology to sail around the world and to win round the world regattas.
All of their interest is focussed on the wind and they need theoretical, but above all practical, knowledge to help them to take the correct decisions at sea.
Remember you can access to the help forum.
If you are experiencing difficulty learning or accessing course content, or if you simply want more information. 14 videos17 readings1 assignment The science of meteorology is a fundamental part of any type of ocean navigation. In the case of yacht racing, it's importance is even greater, given that the wind is the force propelling the boat and is the key factor in formulating the strategy and tactics needed to win. However, the lead role of meteorology in a regatta is for safety, and that is something that the race organisers always make a priority.
In Module 4.1 the general climatology for a regatta such as the Barcelona World Race is described, as well as the preparations the skippers make with the sails, the boat and other personal kit.
In Module 4.2 you will learn how the Race Management of a regatta work together with the meteorologist to ensure that the information reaches the boats and to guarantee the maximum safety levels for the crews.
In Module 4.3 the type of information the crews receive whilst out on the oceans is described, as well as the telecommunications systems used to make this happen.
In Module 4.4 you will learn how weather information impacts on safety and you will look at the specific case of ice detection in the Southern Ocean. 7 videos6 readings1 assignment We begin now by going over the Barcelona World Race round the world route.
In Module 5 you will learn about general and specific strategies for sailing from Barcelona to the Indian Ocean. 7 videos6 readings1 assignment In this module we are going to study the meteorology and strategy for the seas of the south of the planet. Down in the Southern Ocean is where the sailors go up against the toughest sailing conditions in the regatta and where they must also abide by safety restrictions due to the danger of floating ice.
On the following pages, Marcel van Triest will analyse general strategy and also look at case studies from the Barcelona World Race 2010/11. In that edition, ice gates were used to restrict the fleet's descent south and to avoid boats heading into danger zones. For the 2014/15 edition, however, ice gates have been substituted by a “restriction zone”, a polygon with some 72 sides surrounding the Antarctic.
In this video Marcel explains the general context of the passage through the Southern Ocean and reviews the routes taken in the 2010/11 edition of the race. They key difference in this edition is that the regatta does not take the boats through Cook Strait (New Zealand). 6 videos5 readings1 assignment
|
6 modules
| null |
19 hours to complete (3 weeks at 6 hours a week)
|
https://www.coursera.org/learn/meteorology
|
95%
|
702 |
Introduction to Finance and Accounting Specialization
|
72,198
|
4.4
| 2,249 |
Michael R Roberts
|
University of Pennsylvania
|
['Financial Accounting', 'Accounting', 'Decision-Making', 'Corporate Finance', 'Financial Statement', 'Financial Accounting', 'Accounting', 'Decision-Making', 'Corporate Finance', 'Financial Statement']
|
This specialization provides an introduction to corporate finance and accounting, emphasizing their application to a wide variety of real-world situations spanning personal finance, corporate decision-making, financial intermediation, and how accounting standards and managerial incentives affect the financial reporting process. It begins with concepts and applications like time value of money, risk-return tradeoff, retirement savings, mortgage financing, auto leasing, asset valuation, and many others. The specialization uses Excel to make the experience more hands-on and help learners understand the concepts more directly. From valuing claims and making financing decisions, to elements of a basic financial model, the coursework provides a solid foundation to corporate finance. The specialization then moves to financial accounting, enabling learners to read financial statements and to understand the language and grammar of accounting. The coursework introduces bookkeeping fundamentals, accrual accounting, cash flow analysis, among much else! Finally, using the foundational knowledge of accounting, the specialization teaches learners how to understand and analyze key information that companies provide in their statements, including types of assets and liabilities and longer-term investments and debts, and finally the difference between tax reporting and financial reporting. Applied Learning Project This specialization uses a series of homework, quizzes and an optional Excel spreadsheet to help learners gain a more comprehensive understanding of essential concepts of corporate finance and accounting.The coursework introduces bookkeeping fundamentals, accrual accounting, cash flow analysis, and more!From valuing claims and making financing decisions, to elements of a basic financial model, the coursework provides a solid foundation to corporate finance. In this course, you’ll learn the basic fundamentals of corporate finance. Based on the pre-term qualifying courses for Wharton MBA students, Professor Jessica Wachter has designed this course for learners who need a refresher in financial concepts, or for those who are learning about corporate finance for the first time. You’ll identify foundational concepts in corporate finance, such as NPV, Compound and Simple Interest, and Annuities versus Perpetuities. You’ll also learn how to apply the NPV framework to calculating fixed-income valuation and Equity, using hypothetical examples of corporate projects. By the end of this course, you’ll have honed your skills in calculating risk and returns to optimize investments, and be able to assess the right set of financial information to achieve better returns for your firm. This course provides a brief introduction to the fundamentals of finance, emphasizing their application to a wide variety of real-world situations spanning personal finance, corporate decision-making, and financial intermediation. Key concepts and applications include: time value of money, risk-return tradeoff, cost of capital, interest rates, retirement savings, mortgage financing, auto leasing, capital budgeting, asset valuation, discounted cash flow (DCF) analysis, net present value, internal rate of return, hurdle rate, payback period. Master the technical skills needed to analyze financial statements and disclosures for use in financial analysis, and learn how accounting standards and managerial incentives affect the financial reporting process. By the end of this course, you’ll be able to read the three most common financial statements: the income statement, balance sheet, and statement of cash flows. Then you can apply these skills to a real-world business challenge as part of the Wharton Business Foundations Specialization. The course builds on my Introduction to Financial Accounting course, which you should complete first. In this course, you will learn how to read, understand, and analyze most of the information provided by companies in their financial statements. These skills will help you make more informed decisions using financial information.
|
4 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/finance-accounting
| null |
703 |
Business Finance and Data Analysis Fundamentals Specialization
|
3,680
|
4.6
| 43 |
James Weston
|
Rice University
|
['Business Finance', 'Data Analysis']
|
This Specialization is designed to equip you with a basic understanding of business finance, accounting, and data analysis. We've put together these three courses with the explicit intent of helping people prepare for the rigors of a prestigious MBA program, as well as introducing and refreshing basic knowledge and skills for aspiring business leaders. Having taught at Rice for nearly a combined 40 years, professors James Weston and Brian Rountree have found that entering students often lack confidence in some fundamental quantitative skills, as well as struggling with accounting and finance mechanics and terminology. As a result we have put together a series of lectures, plenty of practice opportunities and video walk-throughs that will allow you to confidently take a seat at the leadership table. Applied Learning Project Learners will have the opportunity to practice foundational math skills, familiarize themselves with terminology, and complete scenario-based problems commonly found in finance or accounting courses. More specifically, learners will construct financial statements, navigate key concepts and tools in financial accounting, identify basic principles of financial valuation discounting, perform some data analysis, and more. Financial statements are a key source of information about the economic activities of a firm. This course is a primer on the construction and basic interpretation of financial statements that should provide learners with a rudimentary understanding of the types of information included in the four primary financial statements: balance sheet, income statement, cash flow statement, and statement of stockholders equity. We will spend time recording transactions using accounting terminology and then building financial statements from those transactions to provide you with an understanding of how and why transactions influence the various financial statements. We will focus on the language of accounting including such terms as the accounting equation, debits and credits, T-accounts, journal entries, accruals versus cash flows, and more. By the end of the course learners will be able to understand the basic differences and similarities of the four financial statements, and will have developed a solid foundation to build upon in an introductory financial accounting course at the MBA level. It is ideally suited for those learners that have never taken a financial accounting course before, as well as for those students who would like to refresh their understanding of basic financial accounting concepts. This short course surveys all the major topics covered in a full semester MBA level finance course, but with a more intuitive approach on a very high conceptual level. The goal here is give you a roadmap and framework for how financial professional make decisions. We will cover the basics of financial valuation, the time value of money, compounding returns, and discounting the future. You will understand discounted cash flow (DCF) valuation and how it compares to other methods. We also step inside the mind of a corporate financial manager and develop the basic tools of capital budgeting. We will survey the how, when, and where to spend money, make tradeoffs about investment, growth, dividends, and how to ensure sound fiscal discipline. Our journey then turns to a Wall Street or capital markets perspective of investments as we discuss the fundamental tradeoff between risk and return. We then synthesize our discussion of risk with our valuation framework and incorporate it into series of direct applications to practice.
This course requires no prior familiarity with finance. Rather, it is intended to be a first step for anyone who is curious about understanding stock markets, valuation, or corporate finance. We will walk through all of the tools and quantitative analysis together and develop a guide for understanding the seemingly complex decisions that finance professionals make.
By the end of the course, you will develop an understanding of the major conceptual levers that push and pull on financial decision making and how they relate to other areas of business. The course should also serve as a roadmap for where to further your finance education and it would be an excellent introduction of any students contemplating an MBA or Finance concentration, but who has little background in the area. This course will equip students with the quantitative skills needed to begin any Masters of Business Administration program. The goal is not to build foundational skills or expert mastery but rather, to provide some middle ground to “shake the rust off” skills that a typical MBA student probably knows, but may not have thought about for quite some time. The course provides a quick refresher on top level math and statistics concepts that will be used throughout the MBA curriculum at any school. All of the concepts will be reinforced with practical real-world examples. All calculations, formulas, and data analysis will be performed in Excel, with many detailed demonstrations. For those unfamiliar or less comfortable with spreadsheets, the course will also prepare students with a basic facility for using spreadsheets to solve quantitative business problems. This course has no prerequisites and is intended for any audience.
|
3 course series
|
Beginner level
|
3 months (at 5 hours a week)
|
https://www.coursera.org/specializations/pre-mba-quantitative-skills
| null |
704 |
Policy, Technology, and Carbon Free Cities
|
Enrollment number not found
|
Rating not found
| null |
Shane Casey
|
University of Colorado Boulder
|
['Climate Policy', 'Urban Sustainability', 'Urban Resilience', 'Climate Resilience', 'Sustainable Development']
|
Welcome to Policy, Technology, and Carbon Free Cities, the second course in the Building Sustainable Cities Specialization. This course is intended to build upon foundational concepts introduced in the first course, Climate Resilience and Urban Sustainability. Through Policy, Technology, and Carbon Free Cities, you will gain the ability to apply a comprehensive toolkit of policy and technology innovations to bolster community resilience. You will develop strategies to implement urban sustainability and climate resilience policies effectively and evaluate opportunities to enhance your community through innovative approaches. You will benefit from an in-depth understanding of sustainability practices through case studies and learn how these can be scaled to larger communities. The course uniquely emphasizes the role and authority of local governments and citizens in decision-making processes, equipping you with the skills to engage the public effectively.
Policy, Technology, and Carbon Free Cities stands out by offering insights into cutting-edge and traditional technologies that drive sustainability and resilience. Through interviews with experts and real-world examples, you will explore diverse strategies, including carbon removal and smart city innovations. Additionally, the course examines the impact of local policies on urban development and public health, providing a holistic view of sustainable urban planning. By the end, you will be prepared to create a vision for future cities, leveraging smart technologies and policy innovations to address climate challenges. Welcome to the Policy, Technology, and Carbon Free Cities course. Get started by meeting the instructors, reviewing expectations for the specialization and course, and introducing yourself to the class. 2 videos2 readings1 discussion prompt This module explores sustainability practices in Boulder, Colorado, and examines how these can be scaled to larger communities. It covers the roles of local governments and citizens in sustainability decision-making and strategies for effective public engagement. Through case studies, quizzes, and discussions, you will gain insights into the dynamics of urban resilience and community involvement. 10 videos11 readings4 assignments1 peer review1 discussion prompt This module provides an in-depth analysis of sustainability practices in cities worldwide, focusing on strategies for achieving carbon neutrality. Students will evaluate the costs and benefits of carbon-free versus carbon-intensive cities, utilizing case studies and quizzes to understand the implications of different urban sustainability approaches. The module aims to equip participants with the knowledge to advocate for sustainable city planning in their communities. 7 videos9 readings3 assignments1 peer review1 discussion prompt This module explores the technologies and design innovations that drive resilience and sustainability in urban environments. It examines the benefits of both modern and pre-modern technologies as preferred solutions for urban sustainability. Participants will create a vision for future cities using smart city technologies and policy innovations, integrating historical insights with new advancements to address contemporary sustainability challenges. 6 videos15 readings4 assignments1 peer review1 discussion prompt This module examines policy innovations in sustainable urban development, focusing on best practices in resilience and sustainability policy. It evaluates opportunities for urban sustainability offered by the 2022 Inflation Reduction Act and related programs. Participants will analyze the impact of local policies on urban density, transportation, public health, and climate, using case studies to illustrate effective strategies and outcomes. 5 videos9 readings3 assignments1 peer review1 discussion prompt
|
5 modules
|
Beginner level
|
17 hours to complete (3 weeks at 5 hours a week)
|
https://www.coursera.org/learn/policy-technology-and-carbon-free-cities
| null |
705 |
Introduction to Communication Science
|
137,809
|
4.7
| 1,879 |
Rutger de Graaf
|
University of Amsterdam
|
[]
|
Since Antiquity, scholars have appreciated the importance of communication: as social beings, we cannot exist without communication. We need to interact with people around us, to make sense of the world and to position ourselves in a wider social and cultural reality. In this course, we look at how and why communication evolved as a science and reflect on today’s dominant paradigms. The course also extends beyond the boundaries of communication science itself, exploring dimensions of history, sociology and psychology. Join our class, together with people all over the world. Introduction to Communication Science explores some of the basic theories, models and concepts from the fields of mass, interpersonal and intrapersonal communication. The course begins with a consideration of several basic models, subsequently progressing to the history of communication theory, linear effect-oriented theories, the reception approach and, finally, exploring theories on the production and reinforcement of culture through communication.
Upon completion of this course, students should:
• have knowledge of the history and development of communication science;
• have knowledge of the dominant theoretical approaches within communication science;
• have knowledge and understanding of the most important models and concepts in this field.
Beginning the week of February 16, 2015, you will be able to join Signature Track, a system that verifies your identity when you take an exam. This option will allow you to earn a Verified Certificate, which provides formal recognition of your achievements in the course and includes the University of Amsterdam logo. Before then, you can complete a “test run” of the exam. You can then re-take the exam after the Verified Certificate becomes available. For information regarding Verified Certificates, see https://courserahelp.zendesk.com/hc/en-us/articles/201212399-Verified-Certificates" In this introduction to the course I will briefly introduce the field of communication science and discuss some basic models that will serve as guidelines to the rest of the course. Also, they explore the historical roots of the science of communication. I will discuss the development of communication theory and the evolution of the media landscape in Antiquity, Medieval and Early Modern times. 16 videos8 readings2 assignments The linear effect-oriented approach is discussed and how it developed in the twentieth century. Evolving from a belief in all-powerful effects after World War I to a more nuanced negotiated effects perspective in the sixties. 16 videos3 readings2 assignments This covers theoretical approaches that understand communication processes as social and cultural forces, as building blocks of reality, and a binding element of power in society. 16 videos2 readings1 assignment 1 video2 readings4 assignments
|
4 modules
| null |
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/communication
|
97%
|
706 |
Statistical Thermodynamics: Molecules to Machines
|
13,684
|
3.9
| 50 |
Venkat Viswanathan
|
Carnegie Mellon University
|
[]
|
Modern engineering research focuses on designing new materials and processes at the molecular level. Statistical thermodynamics provides the formalism for understanding how molecular interactions lead to the observed collective behavior at the macroscale. This course will develop a molecular-level understanding of key thermodynamic quantities like heat, work, free energy and entropy. These concepts will be applied in understanding several important engineering and biological applications. 4 videos3 assignments 2 videos1 assignment1 app item 5 videos1 assignment 3 videos1 assignment 3 videos1 assignment 3 videos1 assignment 4 videos 1 video
|
8 modules
|
Intermediate level
|
9 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/statistical-thermodynamics-cm
| null |
707 |
Electric Vehicle Operation and Diagnosis
|
Enrollment number not found
|
Rating not found
| null |
Prasanth Kumar Palani
|
Starweaver
|
['Customer Service and Communication', 'Environmental Awareness and Sustainability', 'Diagnostic and Troubleshooting Skills', 'Technical Understanding of EV Systems']
|
"Electric Vehicle Operation and Diagnosis" is a course tailored to meet the increasing demand for professionals skilled in troubleshooting electric vehicles (EVs). Participants will gain a solid understanding of EV fundamentals, system operations, and diagnostic techniques. The course emphasizes environmental benefits and sustainable practices in transportation. Through practical case studies and real-world examples, participants will learn how to effectively diagnose and resolve common EV issues using specialized tools and techniques. Key topics include high voltage battery management, motor control, and customer service skills. The course targets automotive service technicians, students, and professionals interested in EV diagnosis, accommodating beginner to intermediate levels.
With a duration of 4.0 hours, this course provides concise yet comprehensive training, assuming basic knowledge of electric vehicle architecture and physics terms. It equips learners with the necessary expertise to navigate the complexities of electric vehicles and contribute to the sustainable transportation landscape. Learn the fundamentals of electric vehicles, including their evolution, key components, and basic workings, to establish a foundational understanding of EV technology. 10 videos4 readings1 assignment2 discussion prompts This module provides comprehensive insights into the driving dynamics, energy efficiency, and maintenance requirements of electric vehicles (EVs), equipping learners with the knowledge to operate and maintain EVs effectively while optimizing performance and ensuring longevity. 10 videos3 readings1 assignment2 discussion prompts Module 3 provides a comprehensive overview of basic diagnostics in electric vehicles (EVs), covering the use of diagnostic tools, interpretation of diagnostic codes, common EV issues, system-specific diagnostics, troubleshooting procedures, and customer service aspects. 10 videos3 readings1 assignment2 discussion prompts Advanced EV Diagnostics and Problem Solving delves into sophisticated techniques for diagnosing and addressing complex issues in electric vehicles, preparing technicians for future challenges in the field. 11 videos3 readings1 assignment2 discussion prompts
|
4 modules
|
Beginner level
|
7 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/electric-vehicle-operation-and-diagnosis
| null |
708 |
Learn to Program: The Fundamentals
|
491,767
|
4.7
| 6,545 |
Jennifer Campbell
|
University of Toronto
|
['Python Syntax And Semantics', 'Computer Programming', 'Python Programming', 'Idle (Python)']
|
Behind every mouse click and touch-screen tap, there is a computer program that makes things happen. This course introduces the fundamental building blocks of programming and teaches you how to write fun and useful programs using the Python language. This module gives an overview of the course, the editor we will use to write programs, and an introduction to fundamental concepts in Python including variables, mathematical expressions, and functions. 8 videos10 readings1 assignment This module introduces strings (a Python data type used to represent text), and a process to follow when creating a function. 6 videos6 readings1 assignment1 programming assignment This module introduces Booleans (logical values True and False), how to convert between types, how to use Boolean expressions in if statements to selectively run code, and the concept of a Python module. 7 videos7 readings1 assignment This module introduces one way to repeat code (using a for loop), how to manipulate strings, and how to use a debugger to watch a program execute step by step. 5 videos5 readings1 assignment1 programming assignment This module introduces another way to repeat code (using a while loop), how to properly document your code to help other programmers understand it, Python's list data type, and the concept of mutation. 6 videos6 readings1 assignment This module introduces how to use a for loop over the indexes of a list, how to nest lists, and how to read a write files. 7 videos6 readings1 assignment1 programming assignment This module introduces tuples (an immutable version of lists), and Python's dictionary type. 4 videos3 readings2 assignments
|
7 modules
|
Beginner level
| null |
https://www.coursera.org/learn/learn-to-program
|
94%
|
709 |
Preparing for the SAS Programming Certification Exam
|
6,903
|
4.8
| 136 |
Stacey Syphus
|
SAS
|
[]
|
In this course you have the opportunity to use the skills you acquired in the two SAS programming courses to solve realistic problems. This course is also designed to give you a thorough review of SAS programming concepts so you are prepared to take the SAS Certified Specialist: Base Programming Using SAS 9.4 Exam. In this module you get an overview of this course and set up the data you need for practices and activities. 2 videos4 readings This module is a review of the first three modules of the Getting Started with SAS Programming course. Lectures demonstrate the concepts you learned, and readings from the SAS Certification Prep Guide reinforce those concepts. The review and programming questions assess your understanding of the material. 9 videos3 readings11 assignments This module reviews the preparing, analyzing and exporting modules of the Getting Started with SAS Programming course. Lectures demonstrate the concepts you learned, and readings from the SAS Certification Prep Guide reinforce those concepts. The review and programming questions assess your understanding of the material. 8 videos3 readings14 assignments This module is a review of the first four modules of the Doing More with SAS Programming course. Lectures demonstrate the concepts you learned about for preparing data, and readings from the SAS Certification Prep Guide reinforce those concepts. The review and programming questions assess your understanding of the material. 6 videos4 readings16 assignments This module is a review of the last three modules of the Doing More with SAS Programming course. Lectures demonstrate the concepts you learned about for preparing data, and readings from the SAS Certification Prep Guide reinforce those concepts. The review and programming questions assess your understanding of the material. 6 videos2 readings11 assignments
|
5 modules
|
Intermediate level
|
16 hours to complete (3 weeks at 5 hours a week)
|
https://www.coursera.org/learn/preparing-sas-programming-certification
| null |
710 |
Programming Languages, Part A
|
197,756
|
4.9
| 1,872 |
Dan Grossman
|
University of Washington
|
['Recursion', 'Higher-Order Function', 'Pattern Matching', 'Functional Programming']
|
This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones. This course is neither particularly theoretical nor just about programming specifics -- it will give you a framework for understanding how to use language constructs effectively and how to design correct and elegant programs. By using different languages, you will learn to think more deeply than in terms of the particular syntax of one language. The emphasis on functional programming is essential for learning how to write robust, reusable, composable, and elegant programs. Indeed, many of the most important ideas in modern languages have their roots in functional programming. Get ready to learn a fresh and beautiful way to look at software and how to have fun building it.
The course assumes some prior experience with programming, as described in more detail in the first module.
The course is divided into three Coursera courses: Part A, Part B, and Part C. As explained in more detail in the first module of Part A, the overall course is a substantial amount of challenging material, so the three-part format provides two intermediate milestones and opportunities for a pause before continuing. The three parts are designed to be completed in order and set up to motivate you to continue through to the end of Part C. The three parts are not quite equal in length: Part A is almost as substantial as Part B and Part C combined.
Week 1 of Part A has a more detailed list of topics for all three parts of the course, but it is expected that most course participants will not (yet!) know what all these topics mean. Welcome! Start here! Learn about this course and how it's organized. 7 videos5 readings1 discussion prompt This module contains two things: (1) The information for the [unusual] software you need to install for Programming Languages Part A. (2) An optional "fake" homework that you can turn in for auto-grading and peer assessment to get used to the mechanics of assignment turn-in that we will use throughout the course. You can do this module either before or after watching the first few "actual course content" videos in the next module, but you will want to get the software installed soon so you can learn by actively trying out variations on the code in the videos. You will need to install the software to do the homework. 4 videos3 readings1 programming assignment1 peer review It's time to dive in! Start with a careful reading of the "Section 1 Welcome Message" and go from there. 17 videos6 readings1 programming assignment1 peer review This section is a particularly rewarding one where a lot of ideas come together to reveal a surprisingly elegant underlying structure in ML. As usual, start with the welcome reading, dive into the material, and leave plenty of time to approach the programming assignment methodically. 22 videos6 readings1 programming assignment1 peer review This section is all about higher-order functions -- the feature that gives functional programming much of its expressiveness and elegance -- and its name! As usual, the first reading below introduces you to the section, but it will make more sense once you dive in to the lectures.
Also be sure not to miss the material on course motivation that we have put in a "lesson" between the other videos for this week and the homework assignment. The material is "optional" in the sense that it is not needed for the homeworks or next week's exam, but it is still very highly encouraged to better understand why the course (including Parts B and C) covers what it does and, hopefully, will change the way you look at software forever. 28 videos6 readings1 programming assignment1 peer review We finish Part A of the course with this module. As explained in more detail in the welcome message, we discuss type inference, ML's module system, and the fundamental idea in computing of two computations being equivalent. There is no programming assignment -- instead there is an exam covering all of Part A. Finally, there is a brief wrap-up video for the end of Part A that also looks ahead to Part B and Part C -- we have put it after the exam, so don't overlook it. 19 videos5 readings2 assignments
|
6 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/programming-languages
|
97%
|
711 |
Introduction to Networking
|
17,013
|
4.6
| 260 |
NVIDIA Training
|
NVIDIA
|
[]
|
Welcome to the Introduction to Networking Course. In this course we will cover the basics of networking, introduce commonly used TCP/IP protocols and cover the fundamentals of an Ethernet network.
In addition, you’ll be equipped with the basic knowledge to understand the main data center requirements and how they can be fulfilled.
Upon successful completion of the course's final exam, you will receive a digital completion certificate that confirms your understanding of Ethernet technology basics and data forwarding within an Ethernet network. We will start with what a network is and why it is needed.
Next, we will describe the network components and provide the requirements for a networking solution, especially in highly demanding environments.
We will introduce the OSI model and the TCP/IP protocol suite and their role in networking.
We will cover the basics of Ethernet technology and understand how data is forwarded in an Ethernet network. Lastly, we will learn about the main data center requirements and how they can be fulfilled. 4 videos It is highly recommended that you complete all the course activities before you begin the quiz. Good luck! 1 assignment
|
2 modules
|
Beginner level
|
1 hour to complete
|
https://www.coursera.org/learn/introduction-to-networking-nvidia
| null |
712 |
GitHub Copilot for Project Management
|
Enrollment number not found
|
Rating not found
| null |
Microsoft
|
Microsoft
|
['Visual Studio Code', 'Coding', 'GitHub Copilot', 'Developing with AI', 'GenAI']
|
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 module introduces the use of GitHub Copilot for enhancing code review processes. You will explore practical methods to optimize and improve code quality using AI-driven insights and suggestions. 4 videos2 readings2 assignments This module covers the use of GitHub Copilot for generating comprehensive documentation. You will learn how to leverage AI to enhance knowledge sharing and project maintenance through automated documentation. 4 videos2 readings2 assignments This module focuses on using GitHub Copilot to create detailed development plans. You will explore how AI can assist in strategizing, planning, and executing development processes. 4 videos2 readings3 assignments
|
3 modules
|
Beginner level
|
3 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/github-copilot-for-project-management
| null |
713 |
Large Language Model Operations (LLMOps) Specialization
|
6,747
|
4.6
| 71 |
Derek Wales
|
Duke University
|
['Azure Databricks']
|
Master the world of Large Language Models through this comprehensive specialization from Coursera and Duke University, a top Data Science and AI program. Dive into topics ranging from generative AI techniques to open source LLM management across various platforms such as Azure, AWS, Databricks, local infrastructure, and beyond. Through immersive projects and best practices, gain hands-on experience in designing, deploying, and scaling powerful language models tailored for diverse applications. Showcase your newly acquired LLM management skills by tackling real-world challenges and building your own portfolio as a proficient LLMOps professional preparing you for roles such as Machine Learning Engineer, DevOps Engineer, Cloud Architect, AI Infrastructure Specialist, or LLMOps Consultant. Applied Learning Project Through over 20 hands-on coding projects like deploying large language models on Azure and AWS clouds or services such as Databricks, utilizing the Azure AI Service for building applications, creating powerful prompts with LLM frameworks, running local LLM models using external APIs and cloud services, and constructing a chatbot based on personal data with vector databases, learners will acquire authentic, portfolio-ready experience in deploying, managing, and optimizing large language models. These projects are designed by experts at leading institutions to help professionals tackle real-world LLMOps challenges across various platforms and applications. Learn to utilize Generative AI for automation. Develop Generative AI software solutions. Build solutions with Prompt Engineering to enhance Generative AI output. Gain proficiency in leveraging Azure for deploying and managing Large Language Models (LLMs). Develop advanced query crafting skills using Semantic Kernel to optimize interactions with LLMs within the Azure environment. Acquire hands-on experience in implementing patterns and deploying applications with Retrieval Augmented Generation (RAG) Create and manage data pipelines and their lifecycle Connect and work with message queues to manage data processing Use vector, graph, and key/value databases for data storage at scale Learn to use AWS to build solutions with Generative AI. Learn the basics of AWS cloud computing to enable you to be proficient with machine learning on AWS. Develop machine learning solutions using AWS services like Amazon Bedrock. Use Databricks for data engineering and ML workloads Create and design ML pipelines Use Llamafile and other local LLMs like Mixtral Run local large language models Fine-tune LLMs Use open-source generative AI
|
6 course series
|
Beginner level
|
5 months (at 10 hours a week)
|
https://www.coursera.org/specializations/large-language-model-operations
| null |
714 |
Gemini in Google Sheets
|
Enrollment number not found
|
Rating not found
| null |
Google Cloud Training
|
Google Cloud
|
[]
|
Gemini for Google Workspace is an add-on that provides customers with generative AI features in Google Workspace. In this mini-course, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Sheets. Gemini for Google Workspace is an add-on that provides customers with generative AI features in Google Workspace. In this mini-course, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Sheets. 4 videos1 reading1 assignment
|
1 module
|
Beginner level
|
1 hour to complete
|
https://www.coursera.org/learn/duet-ai-in-google-sheets
| null |
715 |
Advanced Manufacturing Enterprise
|
17,854
|
4.6
| 632 |
Sara Behdad
|
University at Buffalo
|
[]
|
Enterprises that seek to become proficient in advanced manufacturing must incorporate manufacturing management tools and integrate data throughout the supply chain to be successful. This course will make students aware of what a digitally connected enterprise is, as they learn about the operational complexity of enterprises, business process optimization and the concept of an integrated product-process-value chain. Students will become acquainted with the available tools, technologies and techniques for aggregation and integration of data throughout the manufacturing supply chain and entire product life-cycle. They will receive foundational knowledge to assist in efforts to facilitate design, planning, and production scheduling of goods and services by applying product life cycle data.
Main concepts of this course will be delivered through lectures, readings, discussions and various videos.
This is the sixth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA The purpose of this module is to educate students on why a holistic approach is necessary for analyzing the impact of advanced manufacturing on the success of an enterprise. 5 videos5 readings5 assignments The purpose of this module is to provide an overview of product lifecycle and describe the challenges and opportunities that organizations face in adoption of advanced manufacturing technologies. We will discuss the desire for collection of product lifecycle data as well as outline the required features for a highly connected enterprise. In addition, we will provide several examples of information-sharing infrastructures and will elaborate the concept of Product Lifecycle Management (PLM) system. Finally, we will discuss several examples of effective data collection technologies. 5 videos5 readings6 assignments1 discussion prompt In this module, we will introduce the current enterprise management tools (such as ERP, MRP, and MES) that are often employed to integrate capabilities of various entities through the supply chain. We will provide a broad overview of these tools, and will review the capabilities of each of them. 4 videos4 readings5 assignments In this module, we discuss the importance of measuring the performance of supply chains. We will also discuss decision analysis methods and techniques that facilitate decision making through the entire product lifecycle. 4 videos8 readings4 assignments1 discussion prompt
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/advanced-manufacturing-enterprise
|
95%
|
716 |
Business Analysis Fundamentals
|
31,431
|
4.7
| 355 |
Microsoft
|
Microsoft
|
['Stakeholder Communication', 'Business Analysis Concepts', 'Quantitative and Qualitative Analysis Methods', 'Problem Identification and Analysis']
|
If you're interested in a career in business analysis but don't know where to start, you've arrived at the right place! This course has been designed for individuals seeking entry-level positions in Business Analysis. Whether you're a recent graduate, a career changer, or someone looking to kickstart your career in the tech industry, it will provide you with the foundational knowledge and practical skills needed to excel in the field of Business Analysis.
This course is part of a series that offers a good starting point for a career in business analysis. It will help you gain knowledge and skills related to essential business analysis concepts, principles, practical methods, and the responsibilities associated with business analysis. This course also gets you one step closer to the Microsoft Power Platform Fundamentals Certificate, which requires no degree or prior experience.
After completing this course, you’ll be able to:
• Describe basic concepts and principles of business analysis
• Explain the role of a business analyst within an organization
• Identify and analyze a business problem
• Identify and analyze stakeholders in a business project In this module, you’ll explore the essential ideas and rules behind business analysis, including the core concepts and practical methods used in this field. You’ll discover the important responsibilities and tasks associated with this role, and see how it plays a key part in making important decisions and keeping everyone on the same page. 12 videos9 readings4 assignments1 discussion prompt In this module, you will develop the skills to recognize and understand business problems. You'll learn ways to carefully look at and analyze problems so that you can suggest good solutions and contribute to making smart decisions. 17 videos4 readings8 assignments As you work your way through this module, you’ll focus on the people involved in a business project and learn how to identify their interests, expectations, and how much they can influence the project. 8 videos7 readings10 assignments In this module, you’ll put your skills into practice. You’ll reflect on the key learning points that you reviewed during the course and complete the final assessment and hands-on activity. 2 videos3 readings2 assignments1 discussion prompt1 plugin
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/business-analysis-fundamentals
|
96%
|
717 |
Data Collection and Root Cause Analysis
|
Enrollment number not found
|
Rating not found
| null |
Skill-Up EdTech Team
|
SkillUp EdTech
|
['Lean Six Sigma', 'Business Process Mapping', 'DMAIC framework', 'Root cause analysis', 'Critical to quality (CTQ)']
|
The course will equip you with the competencies and essential skills required to excel in the American Society for Quality (ASQ) Certified Six Sigma Yellow Belt (CSSYB) exam and contribute to process improvement programs. This course focuses on various data collection tools and techniques to analyze data, identify the root causes of a problem, and explore the concepts of measurement system analysis (MSA), and hypothesis testing. By the end of this course, you will be able to:
• Define data requirements to gather relevant data from the process using appropriate data collection methods.
• Calculate baseline process performance metrics based on the collected data.
• Analyze data for variations and use data analysis tools and techniques to identify the root causes for the problem or variation.
The course is best suited for entry-level professionals who are new to the world of Six Sigma and wish to improve their professional experience and opportunities. For this course, no prior knowledge is required, however, it is recommended that you complete the first course, Introduction to Lean Six Sigma and Project Identification Methods in the ASQ-Certified Six Sigma Yellow Belt Exam Prep Specialization. This module introduces you to descriptive statistics, a branch of statistics that involves summarizing and describing the main features of a dataset. It provides tools and techniques to organize, present, and analyze data to gain insights into its central tendencies, variability, and distribution. Descriptive statistics is fundamental in data analysis and is a basis for more advanced statistical methods. You will also be introduced to inferential statistics.
The module also explains the various data types and helps you differentiate between qualitative and quantitative data and data coming from internal and external sources. It describes the data collection process. Further, the module delves into the concept of measurement system analysis (MSA) and its components to understand the variations in the measurement process. 7 videos2 readings3 assignments1 discussion prompt This module explains the differences between value-added and non-value-added activities. It makes a case for non-value-added activities that are necessary to enable the smooth running of the organization. The module also discusses how to identify the bottlenecks in a system and suggests ways to eliminate them.
Lastly, the module explores the various techniques to conduct a root cause analysis (RCA) for the identified problem in your process or organization. The first one, Pareto analysis, is based on the Pareto principle, which states that approximately 80% of the effects come from 20% of the causes. This analysis helps prioritize potential root causes based on their relative impact. You will also learn how to use the fishbone diagram, also known as the Ishikawa or cause and effect diagram, which visually represents the potential causes contributing to a problem while categorizing the possible causes into specific groups to facilitate the identification of root causes. Additionally, you will learn about the five whys, a simple yet powerful technique involving repeatedly asking “why” to identify the root cause of a problem. It helps to peel the layers of symptoms and surface-level causes to get to the core issue. 5 videos1 reading3 assignments1 discussion prompt This module provides a comprehensive overview of hypothesis testing, an essential statistical tool used to assess the validity of claims or hypotheses about populations. You will learn about the hypothesis testing process, its application in real-world scenarios, and how to interpret the hypothesis test results to make better decisions. The module will take you through the different types of hypotheses, types of errors, and the significance of the p-value in hypothesis testing.
You will also learn about the principles and applications of correlation and regression techniques. The module discusses the types of correlation and the roles of dependent and independent variables in regression analysis. lt explains the implications of R-squared values in regression analysis. The module also explains simple linear regression and the difference between deterministic and probabilistic models. 8 videos1 reading3 assignments1 discussion prompt This is a peer-review assignment based on the concepts taught in the Data Collection and Root Cause Analysis course. In this assignment, you will apply your knowledge of hypothesis testing to a real-life scenario. 1 video2 readings1 peer review
|
4 modules
|
Beginner level
|
6 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/data-collection-and-root-cause-analysis
| null |
718 |
Soul Beliefs: Causes and Consequences - Unit 3: How Does It All End?
|
11,592
|
4.4
| 94 |
Prof. Daniel M. Ogilvie
|
Rutgers the State University of New Jersey
|
[]
|
Throughout history, the vast majority of people around the globe have believed they have, however defined, a “soul.” While the question of whether the soul exists cannot be answered by science, what we can study are the causes and consequences of various beliefs about the soul and its prospects of surviving the death of the body. Why are soul and afterlife beliefs so common in human history? Are there adaptive advantages to assuming souls exist? Are there brain structures that have been shaped by environmental pressures that provide the foundation of body/mind dualism that is such a prominent feature of many religions? How do these beliefs shape the worldviews of different cultures and our collective lives? What is the role of competing afterlife beliefs in religion, science, politics, and war? This course explores several facets of this relatively unexplored but profoundly important aspect of human thought and behavior. The course consists mainly of 70 to 80 minute lectures, typically broken up into 3 segments, recorded from a course offered by Rutgers University School of Arts and Sciences. These videos include slides and some embedded video clips. Most lectures are accompanied by slides used during the lecture, also including recommended reading assignment which may provide additional opportunities to reflect on your studies.
Due to the lengthiness of this class and natural progression, the online course has been separated into 3 units, this is Unit 3. 1 video2 readings 3 videos1 reading1 assignment 3 videos 4 videos1 assignment 3 videos1 reading 1 video2 readings1 assignment1 peer review 2 videos1 peer review 2 readings
|
8 modules
| null |
13 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/soulbeliefs3
| null |
719 |
Delivery Problem
|
20,913
|
4.7
| 372 |
Alexander S. Kulikov
|
University of California San Diego
|
[]
|
In this online course we’ll implement (in Python) together efficient programs for a problem needed by delivery companies all over the world millions times per day — the travelling salesman problem. The goal in this problem is to visit all the given places as quickly as possible. How to find an optimal solution to this problem quickly? We still don’t have provably efficient algorithms for this difficult computational problem and this is the essence of the P versus NP problem, the most important open question in Computer Science. Still, we’ll implement several solutions for real world instances of the travelling salesman problem. While designing these solutions, we will rely heavily on the material learned in the courses of the specialization: proof techniques, combinatorics, probability, graph theory. We’ll see several examples of using discrete mathematics ideas to get more and more efficient solutions. We start this module with the definition of mathematical model of the delivery problem — the classical traveling salesman problem (usually abbreviated as TSP). We'll then review just a few of its many applications: from straightforward ones (delivering goods, planning a trip) to less obvious ones (data storage and compression, genome assembly). After that, we will together take the first steps in implementing programs for TSP. 4 videos1 reading5 assignments2 ungraded labs We'll see two general techniques applied to the traveling salesman problem. The first one, branch and bound, is a classical approach in combinatorial optimization that is used for various problems. It can be seen as an improvement of the brute force search: we try to construct a permutation piece by piece, but at each step we check whether it still makes sense to continue constructing the permutation (if it doesn't, we just cut off the current branch). The second one, dynamic programming, is arguably the most popular algorithmic technique. It solves a problem by going through a collection of smaller subproblems. 4 videos2 assignments1 ungraded lab As we've seen in the previous modules, solving the traveling salesman problem exactly is hard. In fact, we don't even expect an efficient solution in the nearest future. For this reason, it makes sense to ask: is it possible to find efficiently a solution that is probably suboptimal, but at the same time is close to optimal? It turns out that the answer is yes! We'll learn two algorithms. The first one guarantees to find quickly a solution which is at most twice longer than the optimal one. The second algorithms does not have such guarantees, but it is known to work pretty well in practice. 2 videos1 assignment1 ungraded lab
|
3 modules
|
Beginner level
|
13 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/delivery-problem
| null |
720 |
Managing the Organization
|
49,659
|
4.7
| 1,414 |
Michael Bednar
|
University of Illinois Urbana-Champaign
|
['Organizational Change', 'Decision-Making', 'Strategic Leadership', 'Organizational Culture', 'Ethics']
|
This course is intended to help you become a better manager by helping you more fully understand and deal with the complexities and challenges associated with managerial life in organizations. You will learn theories, principles, and frameworks that will help you more effectively manage and lead your organizations. You will be able to:
- Analyze common managerial challenges and develop solutions to these challenges
- Use power effectively and strategically to implement organizational change
- Understand the foundations of organizational culture and decision-making
- Navigate common decision-making pitfalls and ethical challenges
- Apply principles of organization management to common challenges of management
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/. 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. 4 videos5 readings1 quiz1 discussion prompt This module will introduce you to principles of power so that you can recognize where power comes from and use you power more effectively as a manager. This module will also explore models of organizational change and best practices that can help you successfully implement a change initiative. 9 videos2 readings8 quizzes This module will explore the concept of organizational culture and will help you to understand where it comes from and how you can manage and shape culture in your organization. 5 videos2 readings6 quizzes This module will introduce different types of decision-making processes and will highlight some common decision-making biases that can affect managers, including a number of ethical decision-making traps. 7 videos2 readings7 quizzes1 assignment1 peer review This module will highlight several perspectives on organizational leadership and will use a leadership lens to review key principles that have been discussed in the course. 7 videos4 readings5 quizzes
|
5 modules
|
Beginner level
| null |
https://www.coursera.org/learn/managing-organization
|
96%
|
721 |
Foundations of Marketing Analytics Specialization
|
21,485
|
4.3
| 364 |
David Schweidel
|
Emory University
|
['Basic Descriptive Statistics', 'Market Segmentation', 'Microsoft Excel', 'Marketing']
|
In this specialization you will learn how to: • Find, extract, organize and describe data to support business decisions • Identify, quantify and interpret relationships between variables • Derive customer insights from your data • Develop spreadsheet models to analyze data, evaluate risk and optimize business decisions • Present and justify a course of action to management The capstone project will give you an opportunity to apply what has been covered in the specialization to solve a marketing analytics problem. Applied Learning Project Learners will conduct an exploratory data analysis and examine pairwise relationships among different variables for a marketing analytics problem. At the conclusion of the course, learners will develop and test a predictive model to solve marketing analytics problems. With marketers are poised to be the largest users of data within the organization, there is a need to make sense of the variety of consumer data that the organization collects. Surveys, transaction histories and billing records can all provide insight into consumers’ future behavior, provided that they are interpreted correctly. In Introduction to Marketing Analytics, we introduce the tools that learners will need to convert raw data into marketing insights. The included exercises are conducted using Microsoft Excel, ensuring that learners will have the tools they need to extract information from the data available to them. The course provides learners with exposure to essential tools including exploratory data analysis, as well as regression methods that can be used to investigate the impact of marketing activity on aggregate data (e.g., sales) and on individual-level choice data (e.g., brand choices). To successfully complete the assignments in this course, you will require Microsoft Excel. If you do not have Excel, you can download a free 30-day trial here: https://products.office.com/en-us/try Marketers must make the best decisions based on the information presented to them. Rarely will they have all the information necessary to predict what consumers will do with complete certainty. By incorporating uncertainty into the decisions that they make, they can anticipate a wide range of possible outcomes and recognize the extent of uncertainty on the decisions that they make. In Incorporating Uncertainty into Marketing Decisions, learners will become familiar with different methods to recognize sources of uncertainty that may affect the marketing decisions they ultimately make. We eschew specialized software and provide learners with the foundational knowledge they need to develop sophisticated marketing models in a basic spreadsheet environment. Topics include the development and application of Monte Carlo simulations, and the use of probability distributions to characterize uncertainty. How will customers act in the future? What will demand for our products and services be? How much inventory should we order for the next season? Beyond simply forecasting what customers will do, marketers need to understand how their actions can shape future behavior. In Developing Forecasting Tools with Excel, learners will develop an understanding of the basic components of a forecasting model, how to build their own forecasting models, and how to evaluate the performance of forecasting models. All of this is done using Microsoft Excel, ensuring that learners can take their skills and apply them to their own business problems. How do consumers see your brand relative to your competitors? How should a new product be positioned when it’s launched? Which customer segments are most interested in our current offerings? For these questions and many others, surveys remain the tried and true method for gaining marketing insights. From one-off customer satisfaction surveys to brand tracking surveys that are administered on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers. In Analytic Methods for Survey Data, learners will become familiar with established statistical methods for converting survey responses to insights that can support marketing decisions. Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling. These techniques are presented within the STP (Segmentation, Positioning, Targeting) Framework, enabling learners to apply the analytic techniques to develop a marketing strategy. It is recommended that you complete the Meaningful Marketing Insights course offered by Coursera before taking this course. Note: This course would require using XL Stat, an Excel Add-on that students would need to purchase. XL Stat offers a 30-day free trial, so students could complete this course without incurring additional expense. Social media not only provides marketers with a means of communicating with their customers, but also a way to better understand their customers. Viewing consumers’ social media activity as the “voice of the consumer,” this session exposes learners to the analytic methods that can be used to convert social media data to marketing insights. In Introduction to Social Media Analytics, learners will be exposed to both the benefits and limitations of relying on social media data compared to traditional methods of marketing research. Partnering with a leading social media listening platform, this course provides learners with the foundational skills of social media listening including the creation of monitors and common social media metrics. Moving beyond social media listening, this course shows learners how social media data can be used to provide insights into market structure and consumers’ perceptions of the brand. Learners will have the opportunity to assess data and discern how to "listen" to the data by watching video lectures and completing activities, practice quizzes, discussion boards, and peer assessments. This capstone project will give you an opportunity to apply what we have covered in the Foundations of Marketing Analytics specialization. By the end of this capstone project, you will have conducted exploratory data analysis, examined pairwise relationships among different variables, and developed and tested a predictive model to solve a marketing analytics problem. It is highly recommended that you complete all courses within the Foundations of Marketing Analytics specialization before starting the capstone course.
|
6 course series
|
Intermediate level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/marketing-analytics
| null |
722 |
Microservices and Deployment by using ASP.NET
|
3,039
|
4.3
| 33 |
Board Infinity
|
Board Infinity
|
['Microservices', 'Docker', 'Azure', 'Devops', 'Representational State Transfer (REST)']
|
In this comprehensive course, we delve deep into the concept of microservices using ASP.NET Core, effectively dockerizing .NET Core applications, and utilizing DevOps practices. This course is divided into three core modules. The 'Microservices with .NET Core' module immerses you into the world of microservices, teaching you how to design and develop them, create RESTful APIs, and integrate these services with databases and messaging systems.
The 'Dockerize .NET Core Applications' module elaborates on Docker's pivotal role in containerizing .NET Core applications. It walks you through Docker's foundational concepts and highlights its contribution to deploying and creating robust, production-ready .NET Core applications.
Lastly, the 'DevOps for ASP.NET Core Developers' module presents an overview of DevOps, its principles for efficient software delivery, and the use of Azure DevOps for continuous integration, delivery, automated testing, and monitoring.
By the end of this course, participants will be proficient in building and managing microservices using ASP.NET Core, dockerizing .NET Core applications, and implementing effective DevOps practices in their software development projects. This module provides an overview of microservices architecture using .NET Core. Participants will learn about the benefits and challenges of using microservices, and how to design and implement microservices-based applications using .NET Core. Additionally, the module covers the basic concepts of containerization and orchestration.
This module covers the development of microservices using .NET Core. Participants will learn how to create RESTful APIs, configure services, and use dependency injection to improve code quality and maintainability. Additionally, the module covers the integration of microservices with databases and messaging systems. 19 videos5 readings4 assignments1 discussion prompt The Dockerize .NET Core Applications module is designed to provide a comprehensive guide for developers to containerize their .NET Core applications using Docker. The module covers the fundamental concepts of Docker, including images, containers, and Dockerfiles, and how to use them to deploy .NET Core applications.
Throughout the module, student will learn about important Docker concepts such as Docker registries, networking, and volumes, and how to use them to create production-ready .NET Core applications.
By the end of the Dockerize .NET Core Applications module, developers will have a deep understanding of how to use Docker to containerize their .NET Core applications, and how to deploy and manage them in a production environment. 14 videos4 assignments This module provides an overview of DevOps, including their benefits and how they can be used together to create modern software applications. Participants will learn about the principles of DevOps, including continuous integration and delivery, and how they can be used to deploy and manage microservices-based applications.
This module covers the development of DevOps. Participants will learn how to build microservices using .NET Core, package them as containers, and use Azure DevOps for continuous integration and delivery. Additionally, the module covers the implementation of automated testing and monitoring for microservices-based applications. 13 videos1 reading4 assignments
|
3 modules
|
Advanced level
|
13 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/microservices-and-deployment-by-using-aspnet
| null |
723 |
Tidyverse Skills for Data Science in R Specialization
|
3,159
|
4.6
| 89 |
Stephanie Hicks, PhD
|
Johns Hopkins University
|
['Data Science', 'Data Analysis Software', 'Data Visualization', 'R Programming', 'Predictive Modelling', 'Data Science', 'Data Analysis Software', 'Data Visualization', 'R Programming', 'Predictive Modelling']
|
This Specialization is intended for data scientists with some familiarity with the R programming language who are seeking to do data science using the Tidyverse family of packages. Through 5 courses, you will cover importing, wrangling, visualizing, and modeling data using the powerful Tidyverse framework. The Tidyverse packages provide a simple but powerful approach to data science which scales from the most basic analyses to massive data deployments. This course covers the entire life cycle of a data science project and presents specific tidy tools for each stage. Applied Learning Project Learners will engage in a project at the end of each course. Through each project, learners will build an organize a data science project from scratch, import and manipulate data from a variety of data formats, wrangle non-tidy data into tidy data, visualize data with ggplot2, and build machine learning prediction models. Distinguish between tidy and non-tidy data Describe how non-tidy data can be transformed into tidy data Describe the Tidyverse ecosystem of packages Organize and initialize a data science project Describe different data formats Apply Tidyverse functions to import data into R from external formats Obtain data from a web API Apply Tidyverse functions to transform non-tidy data to tidy data Conduct basic exploratory data analysis Conduct analyses of text data Distinguish between various types of plots and their uses Use the ggplot2 R package to develop data visualizations Build effective data summary tables Build data animations for visual storytelling Describe different types of data analytic questions Conduct hypothesis tests of your data Apply linear modeling techniques to answer multivariable questions Apply machine learning workflows to detect complex patterns in your data
|
5 course series
|
Beginner level
|
2 months (at 10 hours a week)
|
https://www.coursera.org/specializations/tidyverse-data-science-r
| null |
724 |
Optimization for Decision Making
|
6,176
|
4.8
| 66 |
Soumya Sen
|
University of Minnesota
|
['Analytics', 'Linear Programming (LP)', 'Mathematical Optimization']
|
In this data-driven world, companies are often interested in knowing what is the "best" course of action, given the data. For example, manufacturers need to decide how many units of a product to produce given the estimated demand and raw material availability? Should they make all the products in-house or buy some from a third-party to meet the demand? Prescriptive Analytics is the branch of analytics that can provide answers to these questions. It is used for prescribing data-based decisions. The most important method in the prescriptive analytics toolbox is optimization. This course will introduce students to the basic principles of linear optimization for decision-making. Using practical examples, this course teaches how to convert a problem scenario into a mathematical model that can be solved to get the best business outcome. We will learn to identify decision variables, objective function, and constraints of a problem, and use them to formulate and solve an optimization problem using Excel solver and spreadsheet. Prescriptive analytics is a part of business analytics that is aimed at prescribing solutions to decision problems. The most important modeling technique within prescriptive analytics is optimization. In this module, we will learn how to recognize contexts where it can be applied and get introduced to the basics of linear optimization. 11 videos1 reading2 assignments1 discussion prompt In order to solve linear optimization problems (i.e., linear programs), we can use graphical methods for basic example problems. For higher dimensional problems, we will use tools like Excel Solver later in the course. The benefit of using graphical methods is that it gives us an intuition into how these problems can be solved. 8 videos2 assignments In this module we will explore what happens when the model parameters are changed. We will also look at special cases of linear optimization problems. 7 videos2 assignments Having learned how to formulate linear optimization problem and the graphical methods for solving them, we are now going to start solving larger problems using Excel Solver. This module provides an overview of how to set up and solve these decision problems using Excel. 13 videos2 readings2 assignments
|
4 modules
|
Beginner level
|
13 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/optimization-for-decision-making
| null |
725 |
Overcoming Dyslexia
|
47,016
|
4.8
| 858 |
Sally E Shaywitz M.D.
|
Yale University
|
['Education', 'Learning', 'READING', 'Law', 'Dyslexia']
|
Dyslexia is everywhere, touching so many children and adults, and while science has made extraordinary progress in understanding and clarifying the condition, this incredible powerful knowledge rarely reaches those who most need to know and would greatly benefit from it. Our goal is to change all this with the course you are about to view, produced by Dr. Sally Shaywitz, the Audrey G. Ratner Professor in Learning Development, both the leading scientist studying dyslexia and the most devoted advocate for helping those who are dyslexic. The course addresses and answers just about all the questions you have: beginning with what is reading and what is dyslexia and sharing with you the most up-to-date 21st century federal definition of dyslexia. If you are dyslexic, you’ll come to learn you are not alone – dyslexia is very common affecting one out of five, that is, 20% of the population, including both boys and girls all over the world. The course addresses a major question we hear from so many parents and teachers– how do I know if my child may be dyslexic? What signs or symptoms should I be on the lookout for? And here’s another very important question we hear from so many parents and educators who are eager to do the best for their child – when should screening for dyslexia begin? What is the best method? What should I look for or ask about?
A major source of worry for parents is their child’s slow reading- they ask will this prevent a happy future for the child. Yes, dyslexics are slow readers and here, in Coursera, you will come to understand the brain’s role in dyslexia, including slow reading. Great news to share – you will also be so delighted to learn that surrounding a dyslexic’s slow reading is a phenomenal powerful sea of strengths in big picture thinking and reasoning. Dyslexia is a true paradox: dyslexics may be slow readers but at the same time are incredibly fast thinkers!
You can be assured, if you care about a child or someone who is dyslexic and have questions or concerns, you will find it addressed here in this course: everything important to know about and help you select the most effective interventions for a dyslexic child; how to go about choosing the best school, including potentially one that is specialized, for such a child, including what is most important to look for when visiting a potential school; the role of accommodations and how to select the best one; and common co-occurring conditions like ADHD and anxiety – their impact, how to recognize and treat. In the following lessons you will meet wonderful, incredibly insightful and highly successful dyslexics – including governors, cardiac surgeons, nationally renowned attorneys, basketball coaches, economists and dyslexic children and their wonderful families who will share their experiences and advice. Enjoy! In module one, we’ll cover the basics. What is dyslexia? What is reading? How does a dyslexic reader differ from an “automatic” reader? We’ll take some time to talk about the 100+ year history of dyslexia and reveal how much progress modern science has made in understanding what goes on in the brain of a dyslexic reader. 10 videos4 readings1 assignment How does one know if they, or their child, is dyslexic? Module two examines the origin of the difficulties in dyslexia: getting to the sounds of spoken language. . We’ll talk about the paradox of dyslexia: a circumscribed deficit in decoding surrounded by a sea of strengths in higher cognitive function. We’ll examine when, how, and why to begin screening and testing children for dyslexia and what signs primary caretakers and teachers should be on the lookout for in their children and students at risk for dyslexia. 7 videos1 assignment Here we examine the many facets of providing the most effective interventions for dyslexic children. Included are interventions for the beginning reader such as teaching phonemic awareness and phonics. Teaching fluency, vocabulary and comprehension follow as well as strategies that encourage and preserve the child’s self-esteem. Throughout we emphasize the critical importance of employing evidence-based interventions. 9 videos1 assignment We survey and examine public schools, independent schools and schools specialized for dyslexia and when parents of dyslexic children might consider changing their child’s current school. The pros and cons of each type are examined with an emphasis on choosing a school where the climate for dyslexic children is welcoming. Two private independent schools and a public charter school specialized for dyslexia are examined In depth, focusing not only on their reading programs but how these specialized schools preserve and protect the dyslexic child’s self-esteem, promising and most often fulfilling the dyslexic graduate with an opportunity to succeed in high school, college and in life. 9 videos1 assignment Here we use life histories of dyslexic individuals to illustrate how despite their difficulty in reading, by using their sea of strengths and incredible resilience, dyslexics can and do succeed in a wide range of careers and professions. Beginning in adolescence, a focus on academics and organizational skills paves the way to success in college and their perseverance and creativity auger well for their success in the workplace. Through the stories of successful dyslexics we emphasize how critical it is that dyslexic children and young adults know that they can succeed and should be encouraged by their parents, teachers and guidance counselors to pursue their dreams. 8 videos1 assignment Anxiety and ADHD are the most common comorbid disorders co-occurring with dyslexia, anxiety observed in nearly all and ADHD seen in half of children and adults with dyslexia. Through two case histories the subtypes of anxiety (including social anxiety and panic disorder) and the subtypes of ADHD (inattentive, hyperactive-impulsive, combined) as well as their symptoms are reviewd. Effective pharmacologic and non-pharmacologic interventions (cognitive behavioral therapy, CBT, and mindfulness) are reviewed. We emphasize the critical importance of recognizing and treating comorbid anxiety and ADHD in the child and adult with dyslexia. 4 videos1 assignment Dyslexic students and dyslexic adults have come to depend on using technology within a framework of critical accommodations to allow them to succeed not only in school but in their careers and professions. We focus as well on the use of text to speech technology and the accommodation of partial waivers for the foreign language requirement in college and graduate school. In particular we review the rationale including the neural basis for the life-changing accommodation of extra time, especially critical for high stakes, gate-keeper standardized tests. 8 videos1 assignment In these lessons we note the federal definition of dyslexia as “an unexpected difficulty in reading for an individual who has the intelligence to be a much better reader” and review three relevant federal statutes affecting interventions and accommodations for dyslexic students: IDEA, ADAAA, and section 504. We note the concept of condition, manner and duration as detailed in the ADAAA and in the DOJ Final Regulations of that law. We review how the ADAAA has been applied in cases of dyslexic medical and law students requesting accommodations and how dyslexic applicants for high stakes standardized tests no longer suffer the effects of flagging their scores as invalid. 9 videos1 assignment 1 video
|
9 modules
|
Beginner level
| null |
https://www.coursera.org/learn/dyslexia
|
100%
|
726 |
Introduction to Image Generation
|
10,674
|
4.5
| 133 |
Google Cloud Training
|
Google Cloud
|
[]
|
This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI. This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI. 1 video1 assignment
|
1 module
|
Beginner level
|
1 hour to complete
|
https://www.coursera.org/learn/introduction-to-image-generation
| null |
727 |
Introduction to Internet of Things
|
2,133
|
5.0
| 28 |
Prof. Rajbabu Velmurugan
|
IIT Bombay
|
['Sensors', 'Data Analysis Techniques', 'Messaging Protocols', 'Internet of Things (IoT)', 'Sensor Readout', 'Data analysis for IoT', 'Model and Components of IoT', 'Readout Non-Idealities']
|
Enroll in "Introduction to Internet of Things," a meticulously curated course by the eminent faculty of IIT Bombay in conjunction with TIH Foundation for IoT & IoE. This comprehensive course, spanning four modules, equips learners with foundational knowledge and skills essential to navigate the dynamic landscape of IoT. The Learning Objectives of this four-module course led by Prof. Rajbabu Velmurugan, Prof. Laxmeesha Somappa and Prof. Gaurav S. Kasbekar include -
- Understand the fundamental elements and characteristics of IoT including its framework and applications;
- Distinguish between various classifications of sensors and interfaces, comprehend their features and challenges, and evaluate their readouts;
- Analyze the structure and applications of IoT nodes, and apply the essential messaging protocols necessary for IoT; and
- Synthesize knowledge of IoT data analysis methodologies specific to IoT datasets.
Ideal for engineers, IT professionals, tech enthusiasts, and students, this course promises not only theoretical insights but also practical understanding. By the end of the course, participants will emerge as well-rounded IoT professionals, capable of conceptualising, designing, and implementing IoT solutions across diverse sectors. With a blend of rich content, hands-on demonstrations, reading materials, and quizzes, under the mentorship of IIT Bombay's esteemed faculty, this course serves as a beacon for those aspiring to pioneer in the realm of the Internet of Things. Led by Prof. Rajbabu Velmurugan, in the "Internet of Things (IoT): An Introduction" module, learners will embark on a comprehensive journey into the fundamentals of IoT. Lesson 1 delves into the very essence of IoT, exploring its applications and distinct characteristics. Progressing to Lesson 2, participants will uncover the diverse models and components of IoT, enriched with real-world examples like home automation. Concluding with Lesson 3, the module offers an in-depth analysis of IoT architecture and its design goals, ensuring a holistic understanding of the subject. With a well-curated blend of videos and insights, this module serves as an essential primer for anyone keen on grasping the basics of the IoT realm. 14 videos4 readings4 assignments1 discussion prompt Led by Prof. Laxmeesha Somappa, the "Sensors & Interfaces" module offers a comprehensive exploration into the intricate world of sensors, their characteristics, and their interfacing techniques. Lesson 1 serves as a foundational introduction to the realm of sensors, delving into their classifications and providing in-depth case studies on select sensor types like accelerometers, displacement/proximity sensors, and temperature sensors. Building on this foundation, Lesson 2 dives into the vital characteristics that define and differentiate sensors, covering aspects such as sensitivity, accuracy, and response time. The subsequent lessons shift focus to the crucial process of sensor readout, with Lesson 3 elucidating the concepts and design choices surrounding Analog to Digital Conversion (ADC) and quantization, and Lesson 4 highlighting the non-idealities one might encounter, including opamp specific issues. 17 videos4 readings5 assignments Led by Prof. Gaurav S. Kasbekar, the "Networking of IoT Nodes" module delves deep into the mechanisms and challenges of connecting diverse IoT nodes, ensuring seamless communication and data exchange. Lesson 1 lays the foundation by introducing the concept of IoT nodes, their diverse applications in sectors like agriculture, healthcare, smart homes, and infrastructure, and outlines the challenges in their networking. Lesson 2 ventures into low power, low data rate networks, illuminating participants on the IEEE 802.15.4 standard, as well as cutting-edge technologies like LoRa and SigFox. In Lesson 3, the spotlight is on the integration of constrained devices, offering insights into 6LoWPAN, header compression, fragmentation, and routing protocols. Rounding off the module, Lesson 4 dives into messaging protocols essential for IoT, with a comprehensive overview of CoAP and MQTT, their formats, and communication intricacies. 22 videos4 readings5 assignments Led by Prof. Rajbabu Velmurugan, in the "Data Analysis for IoT" module, learners delve into the critical aspects of analyzing vast amounts of data generated by IoT devices. Beginning with an exploration of the significance of data analysis specifically for IoT in Lesson 1, participants will be introduced to the components, feasibility, and various types of learning methods tailored for IoT datasets, with hands-on Python-based implementations. Lesson 2 offers a deeper dive into specific data analysis techniques, encompassing linear regression, time-series models, and clustering methodologies. With a blend of theoretical insights and practical demonstrations, this module ensures that learners are well-equipped to harness the power of data in the IoT domain. Concluding with a special message from the CEO of TIH-IoT. This module is a blend of theoretical knowledge, practical insights, and real-world applications, ensuring learners are well-equipped to navigate the networking landscape of IoT. 13 videos4 readings3 assignments
|
4 modules
|
Intermediate level
|
14 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/introduction-to-internet-of-things
| null |
728 |
Social Determinants of Health
|
6,126
|
4.7
| 34 |
Cleopatra Caldwell
|
University of Michigan
|
['Health Equity', 'social determinants', 'determinants of health']
|
This is an introductory course on social determinants of population health with a focus on the United States. The course will introduce you to, or reinforce your knowledge of, issues related to health that consider behavioral, psychological and structural factors in population health beyond the healthcare system. We will examine social, economic, and political factors that contribute to health inequalities and suggest innovative ways to reduce disparities in health when the goal is to achieve health equity. This course will increase your awareness, knowledge, and understanding of issues related to behavioral, psychological, and structural factors that contribute to understanding population health and health inequities. We will discuss conceptual and methodological issues key to health professionals working towards achieving health equity to reduce health disparities at multiple levels of influence. There will be opportunities to practice skills involving cultural humility, deliberative dialogues and professional self-assessments.
By the end of this course, you will be able to:
Discuss the means by which structural bias, social inequalities and racism undermine health and create challenges to achieving health equity at organizational, community and societal levels In this module, we introduce the concepts of health disparities and health equity, and we examine the historical factors that led to the health disparities we see today. 5 videos7 readings1 assignment1 peer review1 discussion prompt In this module we describe three conceptual frameworks and we examine how they can be usefully applied to understand disparities in mortality and morbidity and to achieve health equity. 3 videos3 readings1 assignment1 peer review1 discussion prompt In this module we apply the social determinants of health framework to the healthcare system, immigration status, and sexual identity, paying special attention to unconscious bias. 3 videos4 readings1 assignment1 peer review1 discussion prompt In this module we dive deeper into racism and discrimination, as well as culture, gender and power, and we examine how we can achieve health equity by changing the structures that reproduce bias and harm health. 6 videos6 readings2 assignments1 peer review
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/social-determinants-of-health
| null |
729 |
Data Processing Using Python
|
107,823
|
4.1
| 357 |
ZHANG Li
|
Nanjing University
|
['Python Programming', 'Numpy', 'Pandas', 'Wxpython']
|
This course (The English copy of "用Python玩转数据" <https://www.coursera.org/learn/hipython/home/welcome>) is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level. This course, as a whole, based on Finance data and through the establishment of popular cases one after another, enables learners to more vividly feel the simplicity, elegance, and robustness of Python. Also, it discusses the fast, convenient and efficient data processing capacity of Python in humanities and social sciences fields like literature, sociology and journalism and science and engineering fields like mathematics and biology, in addition to business fields. Similarly, it may also be flexibly applied into other fields.
The course has been updated. Updates in the new version are :
1) the whole course has moved from Python 2.x to Python 3.x
2) Added manual webpage fetching and parsing. Web API is also added.
3) Improve the content order and enrich details of some content especially for some practice projects.
Note: videos are in Chinese (Simplified) with English subtitles. All other materials are in English. Hi, guys, welcome to learn “Data Processing Using Python”(The English version of "用Python玩转数据", url is https://www.coursera.org/learn/hipython/home/welcome)!In this course, I tell in a manner that enables non-computer majors to understand how to utilize this simple and easy programming language – Python to rapidly acquire, express, analyze and present data based on SciPy, Requests, Beautiful Soup libraries etc. Many cases are provided to enable you to easily and happily learn how to use Python to process data in many fields. 1 video2 readings Hi, guys, welcome to learn Module 01 “Basics of Python”! I’ll first guide you to have a glimpse of its simplicity for learning as well as elegance and robustness. Less is more: the author of Python must know this idea well. After learning this module, you can master the basic language structures, data types, basic operations, conditions, loops, functions and modules in Python. With them, we can write some useful programs! 16 videos7 readings2 assignments1 programming assignment1 discussion prompt Welcome to learn Module 02 “Data Acquisition and Presentation”! After learning this module, you can master the modes of acquiring local data and network data in Python and use the basic and yet very powerful data structure sequence, string, list and tuple in Python to fast and effectively present data and simply process data. 10 videos5 readings1 assignment1 discussion prompt Welcome to learn Module 03 “Powerful Data Structures and Python Extension Libraries”! Have you felt you are closer to using Python to process data? After learning this module, you can master the intermediate-level and advanced uses of Python: data structure dictionaries and sets. In some applications, they can be very convenient. What’s special here is that, you can also feel the charm of such concise and efficient data structures: ndarray, Series and DataFrame in the most famous and widely applied scientific computing package SciPy in Python. 9 videos7 readings1 assignment1 discussion prompt Welcome to learn Module 04 “Python data statistics and mining”! In this module, I will show you, over the entire process of data processing, the unique advantages of Python in data processing and analysis, and use many cases familiar to and loved by us to learn about and master methods and characteristics. After learning this module, you can preprocess the data and fast and effectively mine your desired or expected or unknown results from a large amount of data, and can also present those data in various images. In addition, the data statistics modes of all third party packages in Python are extraordinarily and surprisingly strong, but we, as average persons, can still understand and possess them. 13 videos14 readings2 assignments1 programming assignment Welcome to Module 05 “Object Orientation and Graphical User Interface”! In this module, I will guide you to understand what object orientation is and the relationship between graphical user interface and object orientation. Learners are only required to understand the concepts so that you can more freely and easily pick up various new functions in future. No program writing is required here. Besides, you also need to master the basic framework of GUI, common components and layout management. After learning them, you will find development with GUI is actually not remote. 8 videos5 readings2 assignments
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/python-data-processing
|
92%
|
730 |
Dell Technologies Technical Support Career Introduction
|
Enrollment number not found
|
Rating not found
| null |
Develop with Dell
|
Dell
|
['Career Development', 'job interviews', 'Job Interviews']
|
This course is designed to equip aspiring tech support professionals with the knowledge, skills, and strategies needed to thrive in the fast-paced world of technical support. This course is perfect for individuals looking to start a career in tech support or seasoned professionals aiming to refine their skills and advance their careers. No previous background experience or training is necessary to be successful. Through a series of comprehensive modules, participants will learn about the crucial roles and responsibilities of tech support professionals, the key factors that contribute to success in the field, effective strategies for acing job interviews, and methods for staying current with industry trends. By the end of the course, learners will have a clear understanding of what it takes to excel in tech support and how to position themselves as top candidates in this competitive industry. This week you will get an overview of what a career in Tech Support could look like for you. You’ll learn about what it takes to be a tech support professional and various paths your career could take once you get started. We’ll also discuss some of the key characteristics and qualities needed to be successful in in customer support. You’ll also hear directly from sales managers about what they look for when they interview candidates. 22 videos2 readings4 assignments1 plugin This week is all about the foundational professional skills you’ll need to work in tech support. Things like time management, active listening and communication will be essential to your success as a tech support professional. This week we’ll cover strategies for making the most of your time, and tips for crafting professional business communications. 4 videos1 reading2 assignments1 peer review This week we will explore the critical role of technical support within the dynamic tech industry. You will gain insights into the key role support professionals play in maintaining seamless technology experiences. 1 video1 reading1 assignment1 discussion prompt The need for product knowledge is ever expanding. This week, we will explore strategies for staying up-to-date with industry trends, mastering product features, and fostering a culture of continuous learning. You will discover how product knowledge enhances customer interactions, drives innovation, and contributes to organizational success. 1 video1 reading1 assignment1 peer review
|
4 modules
|
Beginner level
|
8 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/dell-tech-support-career-intro
| null |
731 |
Fundamentals of Business Analysis
|
11,059
|
4.6
| 63 |
Igor Arkhipov
|
Starweaver
|
['Business Analysis', 'Business Analysis Methodology', 'Requirements Analysis', 'Stakeholder Identification', 'Solution Delivery']
|
Learn the fundamental skills for becoming a Business Analyst, including understanding the role of business analysis in the organization, what makes a good business analyst, and gaining a collection of foundational skills used by all the BAs regardless of industry or level of seniority such as: applying analysis to determine the business needs, identifying the stakeholders, gathering and documenting different types of requirements, ensuring the solutions deliver the expected value. The course offers a comprehensive overview of business analysis methodology and approaches.
It combines the theory from industry standards with practical advice and recommendations. You will learn the methodology, the key skills of a BA and the role a Business Analyst plays in the organization.
The course is broken down into 5 main lessons:
• What is business analysis: introduction to the profession and key definitions.
• The core of business analysis: key concepts of business analysis, working with needs, defining the future state, and recommending solutions.
• Scope management: main elements of defining the scope of change, four types of requirements any project has.
• Quality management: the connection between business analysis and quality management, how a BA can contribute to quality.
• Change management: how to deal with change
Content for the course is designed and delivered by Igor Arkhipov who is a certified business analysis professional and industry expert with over 15 years of experience in corporate project environments.
This course is designed for anyone interested in business analysis.
It will be especially useful for aspiring business analysts or other professionals who can benefit from BA skills and methodology, such as project managers, system analysts, change managers, and UX designers.
There are no formal prerequisites for the course, however, some understanding of what is a project and how people usually collaborate in working environments will help. Learn the fundamental skills for becoming a Business Analyst, including understanding the role of business analysis in the organization, what makes a good business analyst, and gaining a collection of foundational skills used by all the business analysts regardless of industry or level of seniority such as: applying analysis to determine the business needs, identifying the stakeholders, gathering and documenting different types of requirements, ensuring the solutions deliver the expected value. 24 videos4 readings7 assignments
|
1 module
|
Beginner level
|
6 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/fundamentals-of-business-analysis
| null |
732 |
Critical Thinking Skills for University Success
|
90,992
|
4.8
| 1,116 |
Katherine Olston
|
The University of Sydney
|
[]
|
In this course, you will learn how to develop your Critical Thinking Skills to help you achieve success in your university studies. After completing this course, you will be able to: 1. Use critical thinking and argumentation in university contexts to improve academic results
2. Understand the importance and function of critical thinking in academic culture
3. Use a variety of thinking tools to improve critical thinking
4. Identify types of argument, and bias within arguments, in order to better evaluate the strength of arguments
5. Use evidence to support claims in arguments
6. Apply critical thinking and argumentation to real world problems and issues 7 videos7 readings6 assignments2 discussion prompts 7 videos4 readings6 assignments2 discussion prompts 6 videos4 readings6 assignments2 discussion prompts 10 videos4 readings6 assignments3 discussion prompts 6 videos4 readings6 assignments2 discussion prompts 4 readings1 peer review2 discussion prompts
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/critical-thinking-skills
|
94%
|
733 |
Meditation: A way to achieve your goals in your life
|
101,044
|
4.6
| 1,011 |
Duck-Joo Lee
|
Korea Advanced Institute of Science and Technology(KAIST)
|
[]
|
Do we truly think that we have lived for ourselves? Perhaps we have lived for money, love, fame, family and pride etc.? Therefore, we don’t seem to be satisfied even though we are full of those things. It is because that we don’t know ourselves. Eric Fromm talked about human nature as two modes of being: “To Have” and “To Be”. If we are “Having” the nature of possessions, we are not satisfied, and feel empty and futile. Then, how can we be “Being” the nature of our inner-selves?
Sometimes, we happened to be aware of this “Being” nature and try to change ourselves, but fail. But, because of our daily routines, it’s easily forgotten. And more it is hard to escape from our unwanted minds controlling us.
From now on, let us reflect on ourselves and look at our minds leading up to today! Don’t we achieve our goals after knowing ourselves? And let us find the “Being” nature of our original selves after escaping from the minds restraining and controlling us.
In this lecture, the definition and principle of the mind are explained in simple and clear ways. You can make sure and practice the methodology of finding the true original mind of inner-self by escaping from the false mind of possession.
Self-reflection is the first step to meditate. You can know yourselves most objectively through meditation and you will realize that all the thoughts and actions are due to your minds which are nonexistent and false. If you throw away the false mind, you will find the true mind.
Meditation is now world-wide sensation. There are many research reports that show people can be leaders if you have a habit of self-reflection through meditation. Now meditation at school and the workplace are popular.
Happiness is having no worries. You can really relax yourself if there is no bundle of thoughts and you can be successful when you know yourself truly. Worries come from the memorized thoughts of the false mind. Your inner potential of positive power are revealed, your peaceful and happiest mind will be in your mind, and you can live the life you wanted through meditation.
This method of meditation is very practical and everybody can follow the methodology. As an engineer, I will guide you step by step to practice this meditation. I am sure that this lecture becomes a turning point in your life. Self- reflection is the methodology of meditation for growth, happiness and human completion: (1) Why do we need self-reflection?, (2) Academic research on self-reflection, (3) Draw my life graph, and (4) Ultimate purpose of self-reflection 6 videos6 readings1 assignment1 discussion prompt Learn the principle of self-reflection and practice the self–reflection through 5 subjects:
(1) Methodology of self-reflection, (2) Practice of self-reflection through 5 essential subjects (barrier in relationships, inferiority and ego in childhood, emotion of love and hatred since childhood, worries, response to problems), and (3) My past life and my current self 9 videos1 reading1 assignment Recognize the copied world and real world and think of living free from the self.: (1) Principle of mind formation, (2) Human recognition observed by philosophers and neuroscientists, (3) Understanding the reasons why we cannot live my own way, and (4) Human mind and Original mind 8 videos1 reading1 assignment Learn and practice the methodology of mind cleansing: (1) Do you want to change yourself?, (2) Methodology of the mind cleansing, (3) Repetition of the self-reflection of the 5 essential subjects, (4) Real potential and positive mind. 8 videos1 reading1 assignment Learn and practice the methodology of self-reflection and the mind cleansing in everyday life: (1)Stress is the impetus for growth, (2) Case study on overcoming the self, (3) Health-mind relationship and brain wave changes, and (4) Meaning of self-reflection and the mind cleansing in life. 7 videos1 reading1 assignment Let’s start the peaceful life with wisdom: (1) Draw your life graph again, (2)People at school and the office practicing self-reflection continuously, (3) Meaning of self-reflection in social aspects (through reflections on communication and relationships), (4) Starting point of the peaceful life with wisdom 7 videos1 reading1 assignment1 discussion prompt
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/self-reflection-meditation
|
97%
|
734 |
Comparative Political Systems
|
2,449
|
4.4
| 25 |
Gianfranco Pasquino
|
Università di Napoli Federico II
|
[]
|
Comparative politics covers a wide variety of topics and themes. The course starts with the definition of the comparative method giving special emphasis to concept formation and historical and institutional approaches. The bulk of the course is devoted to the theory of coalitions and the processes of government formation, functioning, termination. Through several in-depth analyses, the course will throw light on the way democratic regimes are governed. Electoral rules will receive special attention and their impact both on citizens’ behavior and parties and the party system will be thoroughly examined. The types of Parliaments, their structures and their role will be taken into consideration also in order to understand how they affect the formation of governing coalitions. Hence the dynamics and the transformation of those coalitions, with special attention to their more or less frequent rotation in office, will be explored and explained. The assets and the liabilities of the different institutional arrangements will be evaluated. The final part of the course will be devoted to an assessment of the quality of the different democratic regimes and to the proposals for change. The overall picture likely to emerge is that of the existence of several institutional solutions to the challenges and the problems of contemporary democracies. This module presents an initial first exploration of the field of “Comparative Politics”. You will be introduced to comparative politics and the comparative method, and you will understand the nature and components of a political system, and the challenges relating to authorities, recruitment, selection and circulation. 9 videos18 readings3 assignments This module presents one of the three components of the political system: political regimes. You will be introduced to the four types of political regimes, and learn more about parliamentarism, presidentialism and semi-presidentialism. 9 videos14 readings3 assignments This module presents what a party system is and what electoral systems are.You will learn about the classification of party systems, and about the universe of elections. You will then navigate the different types of electoral systems, by analyzing the most basic features of any electoral system from a comparative perspective. 6 videos10 readings2 assignments This module presents and differentiates authoritarian and democratic regimes. You will delve into these two kinds of political regimes, and learn more about authoritarianism, democratization processes, and types of democracies. 6 videos12 readings2 assignments
|
4 modules
|
Beginner level
|
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/comparative-political-systems
| null |
735 |
Mathematics for Machine Learning and Data Science Specialization
|
87,870
|
4.6
| 2,229 |
Luis Serrano
|
DeepLearning.AI
|
['Bayesian Statistics', 'Mathematics', 'Linear Regression', 'Calculus', 'Machine Learning', 'Probability']
|
Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises. As a learner in this program, you'll need basic to intermediate Python programming skills to be successful. Many machine learning engineers and data scientists need help with mathematics, and even experienced practitioners can feel held back by a lack of math skills. This Specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use easy-to-follow visualizations to help you see how the math behind machine learning actually works. We recommend you have a high school level of mathematics (functions, basic algebra) and familiarity with programming (data structures, loops, functions, conditional statements, debugging). Assignments and labs are written in Python but the course introduces all the machine learning libraries you’ll use. Applied Learning Project By the end of this Specialization, you will be ready to: Represent data as vectors and matrices and identify their properties like singularity, rank, and linear independence Apply common vector and matrix algebra operations like the dot product, inverse, and determinants Express matrix operations as linear transformations Apply concepts of eigenvalues and eigenvectors to machine learning problems including Principal Component Analysis (PCA) Optimize different types of functions commonly used in machine learning Perform gradient descent in neural networks with different activation and cost functions Identity the features of commonly used probability distributions Perform Exploratory Data Analysis to find, validate, and quantify patterns in a dataset Quantify the uncertainty of predictions made by machine learning models using confidence intervals, margin of error, p-values, and hypothesis testing. Apply common statistical methods like MLE and MAP Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence Apply common vector and matrix algebra operations like dot product, inverse, and determinants Express certain types of matrix operations as linear transformation, and apply concepts of eigenvalues and eigenvectors to machine learning problems Analytically optimize different types of functions commonly used in machine learning using properties of derivatives and gradients Approximately optimize different types of functions commonly used in machine learning Visually interpret differentiation of different types of functions commonly used in machine learning Perform gradient descent in neural networks with different activation and cost functions Describe and quantify the uncertainty inherent in predictions made by machine learning models Visually and intuitively understand the properties of commonly used probability distributions in machine learning and data science Apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems Assess the performance of machine learning models using interval estimates and margin of errors
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3 course series
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Intermediate level
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3 months (at 5 hours a week)
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https://www.coursera.org/specializations/mathematics-for-machine-learning-and-data-science
| null |
736 |
Recommender Systems Specialization
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19,495
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4.4
| 704 |
Joseph A Konstan
|
University of Minnesota
|
['Evaluation', 'LensKit', 'Collaborative Filtering', 'Recommender Systems', 'Matrix Factorization']
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A Recommender System is a process that seeks to predict user preferences. This Specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative filtering techniques, as well as advanced topics like matrix factorization, hybrid machine learning methods for recommender systems, and dimension reduction techniques for the user-product preference space. This Specialization is designed to serve both the data mining expert who would want to implement techniques like collaborative filtering in their job, as well as the data literate marketing professional, who would want to gain more familiarity with these topics. The courses offer interactive, spreadsheet-based exercises to master different algorithms, along with an honors track where you can go into greater depth using the LensKit open source toolkit. By the end of this Specialization, you’ll be able to implement as well as evaluate recommender systems. The Capstone Project brings together the course material with a realistic recommender design and analysis project. This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. After completing this course, you will be able to compute a variety of recommendations from datasets using basic spreadsheet tools, and if you complete the honors track you will also have programmed these recommendations using the open source LensKit recommender toolkit.
In addition to detailed lectures and interactive exercises, this course features interviews with several leaders in research and practice on advanced topics and current directions in recommender systems. In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. You will explore and implement variations of the user-user algorithm, and will explore the benefits and drawbacks of the general approach. Then you will learn the widely-practiced item-item collaborative filtering algorithm, which identifies global product associations from user ratings, but uses these product associations to provide personalized recommendations based on a user's own product ratings. In this course you will learn how to evaluate recommender systems. You will gain familiarity with several families of metrics, including ones to measure prediction accuracy, rank accuracy, decision-support, and other factors such as diversity, product coverage, and serendipity. You will learn how different metrics relate to different user goals and business goals. You will also learn how to rigorously conduct offline evaluations (i.e., how to prepare and sample data, and how to aggregate results). And you will learn about online (experimental) evaluation. At the completion of this course you will have the tools you need to compare different recommender system alternatives for a wide variety of uses. In this course you will learn a variety of matrix factorization and hybrid machine learning techniques for recommender systems. Starting with basic matrix factorization, you will understand both the intuition and the practical details of building recommender systems based on reducing the dimensionality of the user-product preference space. Then you will learn about techniques that combine the strengths of different algorithms into powerful hybrid recommenders. This capstone project course for the Recommender Systems Specialization brings together everything you've learned about recommender systems algorithms and evaluation into a comprehensive recommender analysis and design project. You will be given a case study to complete where you have to select and justify the design of a recommender system through analysis of recommender goals and algorithm performance. Learners in the honors track will focus on experimental evaluation of the algorithms against medium sized datasets. The standard track will include a mix of provided results and spreadsheet exploration.
Both groups will produce a capstone report documenting the analysis, the selected solution, and the justification for that solution.
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5 course series
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Intermediate level
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2 months (at 10 hours a week)
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https://www.coursera.org/specializations/recommender-systems
| null |
737 |
Adapting to the Effects of Climate Change on Quality of Life
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Enrollment number not found
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Rating not found
| null |
Akito Murayama
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The University of Tokyo
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[]
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In order to deal with global climate change, it is necessary to simultaneously advance both ``mitigation'', which reduces greenhouse gases themselves, and ``adaptation'', which takes measures to reduce the damage caused by climate change. In the field of climate change impact assessment, attention has been focused on the impact on “cities”, and reducing the damage caused by climate change to urban residents and preserving their Quality of Life (QoL) is considered an important issue. In this course, you will learn about the impact of climate change on the QoL of local residents from the perspectives of living comfort, industry, urban structures, land use/urban environment, and traffic/transportation systems. For example, how is QoL defined, and what are the effects of climate change on it? We will also focus on agriculture (fruit tree production) as an industry and learn how to understand local climate change risks. A city has various structures such as buildings and infrastructure. How will climate change affect these stocks? How does climate change affect the heat environment in urban areas, and how can we deal with it in terms of urban development? What are the impacts of climate change on transportation systems, and how should we understand and deal with the risks?
In this course, you will learn about these topics based on the latest knowledge. Welcome to the Coursera!
Dear Students, Welcome to “Adapting to the Effects of Climate Change on Quality of Life”! No particular due date is set for now. When you start the course, please take a few minutes to fill out our pre-course survey in this section. This helps us understand who you are so that we can accommodate you in the best way possible. Thank you for your cooperation. We hope to create a great learning community where we can learn from one another. Please post your questions and thoughts and exchange views on the course topics in the Discussion Forum. Your posts will be occasionally monitored by course staff; however, owing to the large number of students and limited resources, we may not be able to answer all questions. We would appreciate your understanding. Thank you for signing up for the course “Adapting to the Effects of Climate Change on Quality of Life” We hope you enjoy the course! Best Regards, The UTokyo MOOC. 1 video2 readings1 discussion prompt1 plugin This module covers global climate change conditions, climate change conditions in Japan, climate change impacts on people’s lives, climate change risk evaluation (the case study of Japanese mandarin), understanding adaptation challenges through stakeholder interviews, and a summary of them. 9 videos1 assignment This module explores the recent research and development in climate change adaptation in the field of urban planning. After introducing the basics of urban planning and climate change, EcoDistricts is introduced as a model framework to address climate change issues at the district scale. Practices in Nishiki 2 District, Nagoya City is explored with a special focus on climate change impact simulation that enables community stakeholders to discuss about the potential adaptation measures. 6 videos1 assignment The advent of Society 5.0 introduces an integrated approach where technology enhances every aspect of life, emphasizing the importance of adapting to climate change and enhancing disaster resilience. This course delves into how advanced technological innovations, such as CASE (Connected, Automated, Shared, Electrification) and electric vehicles (EVs), are pivotal in developing strategies for increased resilience to environmental challenges. We place a special focus on sectors like ski resorts, which are particularly vulnerable to climate variability. Through examining a variety of adaptive measures—from strengthening infrastructure to comprehensive disaster preparedness—we aim to uncover how modern societies can navigate the challenges posed by climate change. By leveraging cutting-edge technology, the goal is to protect against future environmental threats while promoting sustainable growth. 5 videos1 assignment Promoting longer durability of city is pivotal in fostering a sustainable societal model, shifting away from the prevalent "Flow-based Society" towards a more resilient "Stock-based Society." It's imperative to broaden our sustainability framework to encompass not just energy consumption, CO2 emissions, and climate change but also resource use. Embracing the principles of a Stock-based Society, which prioritizes resource preservation and reuse, can significantly mitigate CO2 emissions by reducing the need for continuous production and minimizing waste generation. 3 videos1 assignment 1 reading 1 plugin
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7 modules
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Beginner level
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7 hours to complete (3 weeks at 2 hours a week)
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https://www.coursera.org/learn/climate-change-adaptation
| null |
738 |
How to Get Into Cloud Computing
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Enrollment number not found
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Rating not found
| null |
Dr Rafael Papallas
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University of Leeds
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['Career Development', 'Cloud Computing']
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Cloud computing gives businesses more flexibility, allowing them to quickly scale resources up to meet business demands without having to invest in physical infrastructure. This allows businesses to accelerate innovation, streamline operations and reduce costs. It is no surprise that cloud computing professionals are in great demand and the sector is expected to grow. This course will help you learn how to navigate the world of cloud computing, delving into its critical role in delivering seamless software and services, such as uninterrupted Netflix streaming and data storage.
You'll learn the fundamental concepts of cloud technologies, explore career opportunities like cloud developer, architect, security engineer, consultant, and administrator, and gain insights into the core skills needed to succeed in the field.
The course guides you on the pathway to a rewarding career in cloud computing, providing practical knowledge on acquiring the necessary skills.
Click Start, a nationwide training programme designed to help young people develop digital skills, offers this course. Click Start offers scholarships giving free access to young people in the UK. Follow the link in the Click Start icon on the top, to check if you are eligible for free access! This week will be an introduction to cloud computing and the kinds of jobs that are available in this area. We will start the week by introducing cloud computing, looking at its current applications and examining the benefits and challenges. We will then visit some popular roles in cloud computing, explaining the responsibilities and the job functions. Let's get started! 3 videos12 readings3 assignments2 discussion prompts In the previous week, we introduced you to cloud computing and the roles available. This week you will hear from professionals from industry (Mark from Amazon Web Services and David from T5 Digital) who will offer you advice and look at the skills you need to build to succeed in a career in cloud computing. The final lesson will dive into real-world examples of cloud computing. 4 videos10 readings4 assignments1 discussion prompt
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2 modules
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Beginner level
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5 hours to complete (3 weeks at 1 hour a week)
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https://www.coursera.org/learn/how-to-get-into-cloud-computing
| null |
739 |
Space is Everywhere
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Enrollment number not found
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Rating not found
| null |
Chris Koehler
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University of Colorado Boulder
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['Music', 'Art', 'Writing', 'Film', 'Journalism']
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You are here! Welcome to Course 4 - Space is Everywhere and the last course of this specialization. You are on the final stretch of this journey to finding your Pathway to Space. The topics of Course 4 span four weeks and nine lessons with 36 learning objectives. This course contains some of my most favorite aha moments in the the entire specialization. I hope that you find them and that they impact you in a positive way. We will discuss how space is communicated through news, art, movies, books, music and more. Space is everywhere in our lives and therefore everyone can be involved in it. So keep up the pace. You can do this. Your reward awaits you, finding your pathway to space. Week 1 - We will start with Space in Journalism with Paul Daugherty where Paul and I will discuss the importance of communicating science and space matters in an engaging and accurate way. Space and Music, with Dr. Jay Keister, explores role music has had and continues to have in our perceptions of space. Both lessons are eye and ear opening.
Week 2 - This week includes two special discussions centered around art. To bring the wonder of space and the science we do to everyone is best done through art. In the Art of Space, Erin Espelie and I discuss the significance of art as effective tool to inspire those interested in space to pursue and/or question it further. Erin is filmmaker and created a film just for this course. Joby Harris and I discuss the significance of Visualizing Space Exploration in his lesson. Joby uses many tools to bring a space mission to life well before it has even been funded. He explains his process and demonstrates some of his creativity in a interesting demonstration.
Week 3 - In this time of history, movies and tv shows play a large role in the visual entertainment of humans and some animals. However before this medium, writings played that role. In this week's lesson we discuss both. With Scott Millspaugh's lesson on Space Through the Ages, we discuss how space and it's influence on society was captured and communicated over great periods of time. And how some of these beliefs lasted over a thousand years. In Space and Movies, Dr. Ernesto Acevedo Muñoz and I discuss the movie that changed everything when it comes to space as well as those before and after.
Week 4 - The last week of lessons. I purposely put them at the end as I feel they are a fitting way to end to this specialization. In Science Fiction, Dr. William Kuskin and I revisit the concept of Space and Wonder and its influence on our imagination. How the power of imagination generates hope for all that wield it. In One Pathway to Space, I walk you through a journey in rocket history and connect that history to one book that shaped humanity's future in space. And last but not least, we end the course and this specialization with one final goodbye to the crew and the USS Pathway to Space. In addition, I have arranged for a very special VIP transporter. It is truly the end but it is also just the beginning. Enjoy! Chris and Paul Daugherty (CUB) explore the tools of an effective science journalist and discover how their reporting on science influences the politics, policy, and public perception of space. [CUB = University of Colorado Boulder] 10 videos1 assignment1 discussion prompt Chris and Dr. Jay Keister (CUB) perform an examination of the ways we use music to think about space, and space to think about music. [CUB = University of Colorado Boulder] 10 videos1 assignment1 discussion prompt Chris and Erin Espelie (CUB) perform an examination of the role of art in space and its influences on our human nature to contribute to the larger understanding of the cosmos and our place in it. [CUB = University of Colorado Boulder] 9 videos1 assignment1 discussion prompt Chris and Joby Harris (JPL) explore, through an artist's perspective, the role art plays in communicating the discoveries and future of space exploration through visualization. [JPL = Jet Propulsion Laboratory] 10 videos1 assignment1 discussion prompt Chris and Dr. Scott Millspaugh (CUB) explore how humanity made sense of our place in space through the ages. [CUB = University of Colorado Boulder] 9 videos1 assignment1 discussion prompt Chris and Dr. Ernesto Acevedo-Muñoz (CUB) discuss an overview of how movies transport our minds and alter our perceptions of space. [CUB = University of Colorado Boulder] 9 videos1 assignment1 discussion prompt Chris and Dr. William Kuskin (CUB) take a look at the role art and science fiction play in shaping and creating new realities and understandings of our world and the cosmos. [CUB = University of Colorado Boulder] 10 videos1 assignment1 discussion prompt Chris provides you with a real life example of how one book influenced three individuals and forever changed humans from cave dwellers to star explorers. 10 videos1 assignment1 discussion prompt Chris and the USS Pathway to Space Crew reflect on our journey together as we review where we have gone and what we have discovered + a very VIP transporter! 6 videos1 assignment1 discussion prompt
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9 modules
|
Beginner level
|
21 hours to complete (3 weeks at 7 hours a week)
|
https://www.coursera.org/learn/space-is-everywhere
| null |
740 |
Process Mining: Data science in Action
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88,378
|
4.7
| 1,217 |
Wil van der Aalst
|
Eindhoven University of Technology
|
['Petri Net', 'Process Modeling', 'Process Mining', 'Data Mining']
|
Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine. All of these applications have in common that dynamic behavior needs to be related to process models. Hence, we refer to this as "data science in action".
The course explains the key analysis techniques in process mining. Participants will learn various process discovery algorithms. These can be used to automatically learn process models from raw event data. Various other process analysis techniques that use event data will be presented. Moreover, the course will provide easy-to-use software, real-life data sets, and practical skills to directly apply the theory in a variety of application domains.
This course starts with an overview of approaches and technologies that use event data to support decision making and business process (re)design. Then the course focuses on process mining as a bridge between data mining and business process modeling. The course is at an introductory level with various practical assignments.
The course covers the three main types of process mining.
1. The first type of process mining is discovery. A discovery technique takes an event log and produces a process model without using any a-priori information. An example is the Alpha-algorithm that takes an event log and produces a process model (a Petri net) explaining the behavior recorded in the log.
2. The second type of process mining is conformance. Here, an existing process model is compared with an event log of the same process. Conformance checking can be used to check if reality, as recorded in the log, conforms to the model and vice versa.
3. The third type of process mining is enhancement. Here, the idea is to extend or improve an existing process model using information about the actual process recorded in some event log. Whereas conformance checking measures the alignment between model and reality, this third type of process mining aims at changing or extending the a-priori model. An example is the extension of a process model with performance information, e.g., showing bottlenecks. Process mining techniques can be used in an offline, but also online setting. The latter is known as operational support. An example is the detection of non-conformance at the moment the deviation actually takes place. Another example is time prediction for running cases, i.e., given a partially executed case the remaining processing time is estimated based on historic information of similar cases.
Process mining provides not only a bridge between data mining and business process management; it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development.
The course uses many examples using real-life event logs to illustrate the concepts and algorithms. After taking this course, one is able to run process mining projects and have a good understanding of the Business Process Intelligence field.
After taking this course you should:
- have a good understanding of Business Process Intelligence techniques (in particular process mining),
- understand the role of Big Data in today’s society,
- be able to relate process mining techniques to other analysis techniques such as simulation, business intelligence, data mining, machine learning, and verification,
- be able to apply basic process discovery techniques to learn a process model from an event log (both manually and using tools),
- be able to apply basic conformance checking techniques to compare event logs and process models (both manually and using tools),
- be able to extend a process model with information extracted from the event log (e.g., show bottlenecks),
- have a good understanding of the data needed to start a process mining project,
- be able to characterize the questions that can be answered based on such event data,
- explain how process mining can also be used for operational support (prediction and recommendation), and
- be able to conduct process mining projects in a structured manner. This first module contains general course information (syllabus, grading information) as well as the first lectures introducing data mining and process mining. 18 videos7 readings2 assignments In this module we introduce process models and the key feature of process mining: discovering process models from event data. 8 videos1 reading2 assignments Now that you know the basics of process mining, it is time to dive a little bit deeper and show you other ways of discovering a process model from event data. 8 videos1 reading1 assignment In this module we conclude process discovery by discussing alternative approaches. We also introduce how to check the conformance of the event data and the process model. 8 videos1 reading1 assignment1 peer review In this module we focus on enriching process models. We can for instance add the data aspect to process models, show bottlenecks on the process model and analyse the social aspects of the process. 9 videos1 reading1 assignment In this final module we discuss how process mining can be applied on running processes. We also address how to get the (right) event data, process mining software, and how to get from data to results. 9 videos2 readings2 assignments
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6 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/process-mining
|
97%
|
741 |
Know Thyself - The Value and Limits of Self-Knowledge: The Unconscious
|
87,172
|
4.7
| 762 |
Mitchell Green
|
The University of Edinburgh
|
[]
|
A challenging but fascinating topic on the way to achieving self-knowledge is the unconscious. For well over a century, psychologists, philosophers, and many others have posited a level of mentality that is not immediately open to introspection; some would even say that certain unconscious elements cannot be known through introspection. This course will examine some of the most influential ideas about the unconscious starting with the work of Sigmund Freud, and follow the development of theories of the unconscious all the way to present research in experimental psychology. But be warned: some of the things you may learn about your unconscious mind may be surprising, and possibly even disturbing! ---
This course was created by a partnership between The University of Edinburgh and Humility & Conviction and Public Life Project, an engaged research project based at the University of Connecticut and funded by a generous grant from the John Templeton Foundation. Here you will get an overview of this course, including the topics covered and questions addressed, as well as what you need complete the course. 3 readings1 discussion prompt In this first week of the course we will acquaint ourselves with the ideas of Sigmund Freud, who is probably the most famous advocate and practitioner of psychoanalysis. Shockingly for his time, Freud proposed that many facts of human behavior, including the mistakes we make, what we dream, as well as much behavior that seems on the surface to be irrational, are to be explained as being due to forces in our minds of which we are not conscious. We will look at Freud's reasons for this hypothesis and consider whether those reasons are compelling. 9 videos8 readings5 assignments5 discussion prompts In this second week of the course we explore some developments in psychoanalytic theory that were dominant in the middle of the 20th Century. Focusing on the work of Anna Freud (Sigmund Freud's youngest daughter) and Melanie Klein, we will consider some psychoanalytic themes that emerged after Sigmund's death. Both of A. Freud and Klein were intensely interested in the psychological development of children, and we will learn about some of their ideas on this topic. Also, we will consider some phenomena that have potential resonance for our daily lives such as transference, reaction-formation, and what is now termed "gaslighting". 8 videos8 readings5 assignments4 discussion prompts Much of the last three decades of research related to the unconscious mind has focused on its automatic character, and draws attention to the vast extent of cognitive and affective processing that occur with little or no conscious effort. Such processing is thought to have been evolutionarily adaptive in the past, as well as to simplify our daily lives even now. But these processes can also be hard to modify if they are not working for us, and may account for certain biases that seem to perpetuate some current forms of injustice in many of the world's societies. In this third week of the course we will learn about the "adaptive unconscious", paying attention both to the benefits it confers and the challenges it raises. 11 videos7 readings5 assignments4 discussion prompts In this final module we will consider the relation between emotions and rationality. These are popularly thought to be at odds with one another, and many people hold that to be rational, one must keep emotions at bay. With a focus on the work of neuroscientist Antonio Damasio, we will consider reasons for thinking that one important kind of rationality could not function properly without emotions. 11 videos7 readings5 assignments3 discussion prompts Apply your knowledge of the unconscious! 5 readings1 peer review1 discussion prompt
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6 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/know-thyself-the-unconscious
|
97%
|
742 |
Federal Taxation I: Individuals, Employees, and Sole Proprietors
|
37,488
|
4.9
| 643 |
Matthew Hutchens
|
University of Illinois Urbana-Champaign
|
['Tax Deduction', 'Form 1040 Preparation', 'Individual Taxation', 'U.S. Federal Tax', 'Tax Deductions', 'Self-Employment Tax']
|
This course is the first course in a five-course US Federal Tax Specialization. It covers and focuses on the U.S. federal tax system as it relates to individuals, employees, and sole proprietors. Key concepts covered include gross income and items that are statutorily included or excluded in it, personal and business expenses that qualify as tax deductions, and the differing tax treatments for employees versus self-employed taxpayers. Unlike many other introductory courses in tax and as part of this course’s comprehensive wrap-up, learners will be provided with practical and tangible experience reporting both income and expenses on the main individual tax return used in the US, Form 1040. If you have enjoyed this course, consider enrolling in our online graduate Accounting program. The University of Illinois at Urbana-Champaign, consistently ranked as one of the nation's top three accounting programs, now offers a master’s in accounting at a very affordable tuition rate and is completely online. The iMSA is a full Master of Accountancy program and students graduate with an MS that is highly recognized. Try an open course or two, then apply for admission into the credit-bearing version as you may be eligible to take credit-bearing courses during the application process. If you are missing any prerequisites for the full degree, you can complete Coursera courses to demonstrate readiness and strengthen your application for the iMSA. For more information on this exciting iMSA online program, refer to this link: https://www.coursera.org/degrees/imsa In this module, you will become familiar with the course, your instructor and your classmates, and our learning environment. This orientation will also help you obtain the technical skills required to navigate and be successful in this course. 4 videos4 readings1 discussion prompt In this module, you will be introduced to the different kinds of taxes faced by US taxpayers and the US federal income tax structure. The origin of tax law and its constitutionality is discussed along with a brief history of the different changes in rates that have occurred since the 16th Amendment was passed. Finally, we will discover the three different sources of new tax laws and rules. 12 videos6 readings9 quizzes1 assignment1 discussion prompt In this module, we will take a deeper dive into each part of the US federal income tax structure, with a focus on what is included in gross income. We will learn how for-AGI deductions reduce gross income to generate adjusted gross income, or AGI, and why AGI is an important number that determines the floors and ceilings of many from-AGI deductions. We will also discuss who qualifies as a dependent. We will wrap up the module with a discussion of the actual calculation of the tax as well as filing status and filing requirements. 10 videos9 readings7 quizzes1 assignment In this module, you will take a deeper dive into gross income, specifically regarding statutory inclusions. Congress, the courts, and the IRS have specific rules on whether and when certain income items are included as gross income. These rules provide clarification in situations where it is unclear whether money or property received should actually be included as income. 6 videos1 reading7 quizzes In this module, you will take a deeper dive into gross income, specifically regarding statutory exclusions. Congress, the courts, and the IRS allow exclusions of money or property received by the taxpayer for various reasons. 5 videos2 readings6 quizzes In this module, you will learn about deductions, which is the term used in tax to describe an expense that is allowed to reduce a taxpayer’s tax liability. You will discover what adjusted gross income is, why it is important, and how to calculate it. You will also learn the difference in tax treatments for special types of activities, such as hobbies and rentals. 8 videos1 reading9 quizzes1 discussion prompt In this module, we discuss several unique situations where the same expense may or may not be deductible, dependent on the facts and circumstances surrounding the situation. We will also learn about another from AGI deduction, the new 20% deduction for qualified business income. Finally, we will discuss other business deductions such as bad debts and net operating losses. 9 videos3 readings8 quizzes In this module, we first turn our focus to expenses that qualify as itemized deductions, which are a from AGI deduction. To finish off this module, we’ll switch back to discussing income and situations where taxpayers can elect to delay recognition of income, such as saving for retirement, as well as situations where taxation of the annual earnings of those retirement savings are either deferred or permanently excluded from income. 7 videos8 readings8 quizzes In this module, you will review the Comprehensive Example video and then learn to apply the concepts to a tax return problem. 1 video6 readings5 assignments1 discussion prompt1 plugin
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9 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/federal-taxation-individuals
|
97%
|
743 |
Sales Fundamentals
|
2,361
|
4.9
| 16 |
Dennis Russell
|
Keller Williams
|
['Client Experience', 'Effective Communication', 'Prospecting Strategies', 'Marketing Strategy', 'Lead Conversion']
|
In the Sales Fundamentals course, you will build on and apply the previously learned concepts of lead generation and database management to obtain a deeper understanding of how real estate agents work with leads and how agents convert leads to potential, current, and future business. You will also learn how agents create a lasting client experience that fosters long-term relationships and continuously feeds new leads into their business. Additionally, you will explore the opportunity to grow a business with the rental market. By the end of this course, you'll be able to explain how real estate agents:
1. Generate leads through a variety of methods and convert those leads to appointments.
2. Manage leads in a database.
3. Construct a customer experience centered around business growth.
4. Compose brand standards that enhance the customer experience.
5. Grow a real estate business with a variety of different referral types.
6. Leverage the business opportunities of working with rental properties and leases. Welcome to Focus Your Lead Generation and Conversion, the first module of Sales Fundamentals. This module will build on the concepts of lead generation from the first course. You will learn more about what happens after you generate a lead, what it takes to convert a lead, and how to be purposeful about your lead generation efforts. 19 videos12 readings4 assignments2 discussion prompts Welcome to Maximize Your Database, the second module of Sales Fundamentals. This module will build on the concepts of building a database from the first course. You will learn more about managing your database and communicating with your database to leverage new, repeat, and referral business. 10 videos3 readings3 assignments Welcome to Create Clients for Life, the third module of Sales Fundamentals. In this module, you will learn about client experience and its potential to impact business. You will consider what potential client experience you would want your clients to experience when working with you. You will explore effective communication methods and how you can combine client experience with effective communication to surpass expectations before, during, and after the transaction process. 16 videos8 readings4 assignments2 discussion prompts Welcome to Construct Cohesive Branding and Marketing, the fourth module of Sales Fundamentals. In this module, you will learn about the different components that come together to make a cohesive brand. You will learn about value propositions and create your own for your potential future career in real estate. You will learn more about the impact of social media when marketing a brand. 10 videos7 readings3 assignments1 discussion prompt Welcome to Grow Your Business with Relationships, the fifth module of Sales Fundamentals. In this module, you will learn how establishing relationships outside of the clients in your database can help you grow your business. You will also learn about the referral opportunity and how to maintain relationships that continue to bring you referral business. 11 videos4 readings3 assignments Welcome to Grow Your Business with the Real Opportunity, the final module of Sales Fundamentals. In this module, you will learn about the rental opportunity from two different viewpoints. First, you will learn how a real estate agent can help current homeowners rent the properties they own. Second, you will learn how a real estate agent can help people looking to rent a variety of property types. Finally, you will learn how a real estate agent can take advantage of the opportunities that come from property management. 12 videos3 readings4 assignments Please watch and read the review materials for Sales Fundamentals before beginning the Peer Review Project. 1 video1 reading1 peer review
|
7 modules
|
Beginner level
|
26 hours to complete (3 weeks at 8 hours a week)
|
https://www.coursera.org/learn/sales-fundamentals
| null |
744 |
Machine Learning Foundations for Product Managers
|
45,457
|
4.6
| 464 |
Jon Reifschneider
|
Duke University
|
['Modeling', 'Predictive Analytics', 'Data Science', 'Artificial Neural Network', 'Machine Learning']
|
In this first course of the AI Product Management Specialization offered by Duke University's Pratt School of Engineering, you will build a foundational understanding of what machine learning is, how it works and when and why it is applied. To successfully manage an AI team or product and work collaboratively with data scientists, software engineers, and customers you need to understand the basics of machine learning technology. This course provides a non-coding introduction to machine learning, with focus on the process of developing models, ML model evaluation and interpretation, and the intuition behind common ML and deep learning algorithms. The course will conclude with a hands-on project in which you will have a chance to train and optimize a machine learning model on a simple real-world problem. At the conclusion of this course, you should be able to:
1) Explain how machine learning works and the types of machine learning
2) Describe the challenges of modeling and strategies to overcome them
3) Identify the primary algorithms used for common ML tasks and their use cases
4) Explain deep learning and its strengths and challenges relative to other forms of machine learning
5) Implement best practices in evaluating and interpreting ML models In this module we will be introduced to what machine learning is and does. We will build the necessary vocabulary for working with data and models and develop an understanding of the different types of machine learning. We will conclude with a critical discussion of what machine learning can do well and cannot (or should not) do. 10 videos3 readings1 assignment In this module we will discuss the key steps in the process of building machine learning models. We will learn about the sources of model complexity and how complexity impacts a model's performance. We will wrap up with a discussion of strategies for comparing different models to select the optimal model for production. 8 videos1 reading1 assignment In this module we will learn how to define appropriate outcome and output metrics for AI projects. We will then discuss key metrics for evaluating regression and classification models and how to select one for use. We will wrap up with a discussion of common sources of error in machine learning projects and how to troubleshoot poor performance. 8 videos1 reading1 assignment1 discussion prompt In this module we will explore the use of linear models for regression and classification. We will begin with introducing linear regression and continue with a discussion on how to make linear regression work better through regularization. We will then switch to classification and introduce the logistic regression model for both binary and multi-class classification problems. 6 videos1 reading1 assignment We will begin this model with a discussion of tree models and their value in modeling compex non-linear problems. We will then introduce the method of creating ensemble models and their benefits. We will wrap this module up by switching gears to unsupervised learning and discussing clustering and the popular K-Means clustering approach. 7 videos1 reading1 assignment Our final module in this course will focus on a hot area of machine learning called deep learning, or the use of multi-layer neural networks. We will develop an understanding of the intuition and key mathematical principles behind how neural networks work. We will then discuss common applications of deep learning in computer vision and natural language processing. We will wrap up the course with our course project, where you will have an opportunity to apply the modeling process and best practices you have learned to create your own machine learning model. 9 videos2 readings1 assignment1 peer review
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/machine-learning-foundations-for-product-managers
|
92%
|
745 |
Cosmetic Product Development
|
2,437
|
4.7
| 24 |
Dr. Rolanda Wilkerson
|
Olay
|
['Launching Products', 'Stability Testing', 'Cosmetic Product Formulation']
|
In the third course, Cosmetic Product Development, we analyze every step of developing cosmetic products. We cover everything, including how you would generate ideas, how you know what the customer wants, and feasibility studies. We strongly emphasize collaboration and prototype development, along with how we design and select cosmetic packaging. We engage with raw material suppliers and navigate international manufacturing regulations. You will also learn to evaluate cosmetic product performance, market trends, and sustainable practices. We designed this course to give you a holistic understanding of the cosmetic product development process within industry standards.e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming. This module will delve into customer needs and idea generation, exploring consumer psychology, data collection methods, and innovative idea-generation techniques. Feasibility studies and conceptualization play an important role in developing a new product, and we will evaluate product design principles, idea viability, and proof of concept. The module concludes with prototype development and refinement, emphasizing collaboration, prototype creation steps, and adjustments based on feedback. 12 videos6 readings4 assignments1 discussion prompt In this module, you will embark on the exciting journey of cosmetic product development. Starting with design and material selection for packaging, we'll explore packaging functional design principles, the importance of evaluating costs and benefits, and delve into sustainability practices. Moving on to the manufacturing process, we'll uncover the steps involved in manufacturing cosmetics, learn more about different types of raw material suppliers and how to engage with them, look at the process of scaling production from laboratory batch through to a manufacturing run and explore good manufacturing practices (GMP). Lastly, we'll cover safety standards, legal insights, international regulations, and labeling compliance, and address how to tackle compliance issues effectively. 11 videos1 reading4 assignments2 discussion prompts This module will explore the essential aspects of performance evaluation in cosmetic product development. Beginning with stability testing, we'll clarify various types of product testing, and delve into techniques for performance evaluation, focusing on diverse cosmetic products' evaluation methodologies. Building on this, we'll discuss adjusting based on performance evaluation, demonstrating the process of modifying products based on compiled data. To ensure consistent product quality, we'll outline the necessary steps for maintaining quality control. Additionally, we'll cover ethical testing to ensure products align with legal and ethical standards. Shifting our focus to product launch, we'll explore preparation steps, roll-out strategies, and supply chain management for risk reduction and efficiency, followed by post-launch evaluation techniques and consumer feedback analysis for continuous improvement. 8 videos2 readings3 assignments1 discussion prompt In this module, we explore the diverse aspects involved in developing cosmetic products. We'll assess the formula's alignment with current market needs by reviewing trends and gauging its success accordingly. You'll discover why when looking for methods to maximize and differentiate, the assessment of novel materials is essential. To make your formulas environmentally friendly, we will also examine several methods for ensuring formula optimization, comprehend the fine line that separates quality from cost, assess different formula designs, and investigate sustainable applications. 7 videos2 readings5 assignments1 discussion prompt
|
4 modules
|
Beginner level
|
12 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/cosmetic-product-development
| null |
746 |
Road Safety & Indigenous Communities: Safe Systems Approach
|
Enrollment number not found
|
Rating not found
| 2,024 |
Jeffrey Michael, EdD
|
Johns Hopkins University
|
[]
|
Motor vehicle traffic deaths affect indigenous communities at a disproportionate rate as compared to the overall United States population. For children and youth ages 0-19, motor vehicle traffic death rates among American Indian and Alaska Native children and youths are up to 8 times higher than those of other racial and ethnic groups. This is often due to structural barriers in tribal communities such as lack of lighting, potholes, cattle, etc. This course dives specifically into the effectiveness of taking a Safe Systems approach to road safety in tribal communities. Perspectives from Safe Systems experts and tribal partners on safe systems approaches to road safety are highlighted as examples from specific communities. The course provides historical context to road safety and specific considerations for roads in tribal nations. Next, the course focuses on how to intervene to create a safe system in communities. In addition, this course will prepare you with information on how to apply for an SS4A grant, with examples from specific communities who have successfully obtained the grant. Throughout the course, resources are provided with tools on how to apply for SS4A grant and how to implement a safe systems approach. 7 videos10 readings 2 videos1 reading2 discussion prompts1 plugin 3 videos6 readings2 discussion prompts
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3 modules
| null |
4 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/road-safety--indigenous-communities-safe-systems-approach
| null |
747 |
Deploy AI Apps with Cloudflare
|
Enrollment number not found
|
Rating not found
| null |
Guil Hernandez
|
Scrimba
|
['API Management']
|
Dive into deploying secure and robust applications with our Cloudflare course. Learn to manage API requests with Cloudflare workers, boost app strength with an AI Gateway, and launch websites using Cloudflare Pages. This hands-on course also teaches you to refine error handling for smoother user experiences. Build practical skills in using Cloudflare’s features to secure APIs, enhance sites with AI, and ensure reliability. By the end of the course, you'll be skilled at using Cloudflare to boost your applications' security and performance, ready to solve real-world problems. Learn how to leverage Cloudflare's powerful edge computing and security features to deploy AI applications with high availability and low latency. 1 reading1 assignment14 plugins
|
1 module
|
Intermediate level
|
3 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/deploy-ai-app-with-cloudflare
| null |
748 |
Intro to Operating Systems 3: Concurrency
|
8,866
|
4.4
| 29 |
Patrick Ester
|
Codio
|
['Concurrency', 'Operating Systems']
|
Learn the inner workings of operating systems without installing anything! This course is designed for learners who are looking to maximize performance by understanding how operating systems work at a fundamental level. The modules in this course cover concurrency, threads, locks, locking data structures and multi-CPU scheduling.
To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to slowly building features, resulting in large coding projects at the end of the course. 2 readings1 app item 5 readings4 app items 5 readings4 app items 5 readings4 app items
|
4 modules
|
Advanced level
|
7 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/codio-intro-to-operating-systems-3-concurrency
| null |
749 |
Behavioral Finance
|
171,450
|
4.4
| 4,117 |
Emma Rasiel
|
Duke University
|
['Decision-Making', 'Behavioral Finance', 'Finance', 'Cognitive Bias', 'Behavioral Economics']
|
We make thousands of decisions every day. Do I cross the road now, or wait for the oncoming truck to pass? Should I eat fries or a salad for lunch? How much should I tip the cab driver? We usually make these decisions with almost no thought, using what psychologists call “heuristics” – rules of thumb that enable us to navigate our lives. Without these mental shortcuts, we would be paralyzed by the multitude of daily choices. But in certain circumstances, these shortcuts lead to predictable errors – predictable, that is, if we know what to watch out for. Did you know, for example, that we are naturally biased towards selling investments that are doing well for us, but holding on to those that are doing poorly? Or that we often select sub-optimal insurance payment plans, and routinely purchase insurance that we don’t even need? And why do so many of us fail to enroll in our employer’s corporate retirement plans, even when the employer offers to match our contributions? Behavioral finance is the study of these and dozens of other financial decision-making errors that can be avoided, if we are familiar with the biases that cause them. In this course, we examine these predictable errors, and discover where we are most susceptible to them. This course is intended to guide participants towards better financial choices. Learn how to improve your spending, saving, and investing decisions for the future. Welcome to the course! In this first week, we'll look at the classical economic model of consumer choice, which assumes that all of the decisions that we make are sensible, or “rational.” Once we have examined the underlying theory of how people should behave (especially around financial decisions), we will move on to examine how people do behave. We will focus in particular on situations in which we are most inclined to make decisions that appear to defy rational choice axioms. 5 videos4 readings1 assignment Welcome to the second week. In this session, we will discover how our minds are inclined to distort probabilities, and either underestimate or overestimate the likelihood of certain outcomes. We’ll also learn about “heuristic-driven bias”: the tendency to use rules of thumb that simplify the process of making decisions, but can also lead to predictable errors. These biases negatively affect our decision-making far more than we might expect; especially when the outcome of the decision has great significance for us. 8 videos6 readings1 assignment In the final week of the course, we will see multiple examples of how mental heuristics can lead us to make predictably sub-optimal financial decisions, both individually and across the entire financial markets. We will also discuss the many ways in which you can now improve your financial decision-making because of your deeper understanding of the innate biases that have tripped you up in the past! 2 videos2 readings1 assignment
|
3 modules
|
Beginner level
| null |
https://www.coursera.org/learn/duke-behavioral-finance
|
96%
|
750 |
Data Driven Decision Making
|
Enrollment number not found
|
4.8
| 17 |
Wendy Martin
|
University of Colorado Boulder
|
['Probability And Statistics', 'Data-Informed Decision-Making', 'Data Analysis', 'Data Visualization']
|
Once we have generated data, we need to answer the research question by performing an appropriate statistical analysis. Engineers and business professionals need to know which test or tests to use. Through this class, you will be able to perform one sample tests for comparison to historical data. You will also be able to determine statistically significant relationships between two variables. You will be able to perform two sample tests for both independent and dependent data. Finally, you will analyze data with more than two groups using the Analysis of Variance. 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. Upon completion of this module, students will be able compare generated data to historical data for both continuous and discrete data using RStudio and ROIStat. 16 videos1 reading1 quiz2 discussion prompts Upon completion of this module, students will be able to determine relationships between two variables for both continuous and discrete data using RStudio and ROIStat. 10 videos1 quiz1 discussion prompt Upon completion of this module, students will be able to compare two independent samples for both continuous and discrete data using RStudio and ROIStat. 15 videos1 quiz1 discussion prompt Upon completion of this module, students will be able to compare two dependent samples for both continuous and discrete data using RStudio and ROIStat. 18 videos1 quiz1 discussion prompt Upon completion of this module, students will be able to analyze continuous data with more than 2 groups using RStudio and ROIStat. 13 videos1 quiz1 discussion prompt
|
5 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/data-driven-decision-making
| null |
751 |
Biostatistics Study Design and Analysis for Grant Writing
|
Enrollment number not found
|
Rating not found
| null |
Anne M. Libby, PhD
|
University of Colorado System
|
['Medical Research', 'Statistical Analysis', 'Biostatistics', 'Grant Writing', 'Biomedical Sciences']
|
This course is targeted to early career and novice researchers writing their first major competitive biomedical / health research grant proposals. After the course, you will be able to: 1) Identify and summarize key decisions in study design that align scope and complexity with budget and timeline;
2) Describe key variables and their relationships to each other; and
3) Interpret essential parts of a power analysis and summarize appropriate questions for an expert biostatistician.
We are faculty at a major research institution with proven experience training others to health sciences research career success. Study design and analysis planning are key skills for grant writing. This course is part of a larger Specialization called Grant Writing for Health Researchers. Please consider taking the other two courses on (1) Grant proposal plans, sections, and resubmission, and (2) Scientific writing. Together, these have been a recipe for success for researchers at the University of Colorado and beyond. Upon completion, you will earn an e-badge to display your new skills. Please join us! Learn how your choices on study design affect project scope, especially data collection, intervention type, and timeline. 7 videos1 reading1 assignment Learn to characterize key variables by the roles they play in your research questions. 8 videos1 reading1 assignment Learn how to prepare the component parts of an analysis plan. 4 videos1 reading1 assignment Learn key parts of power analyses in grant proposals and how to isolate unknown values. 7 videos3 readings1 assignment Learn differences in statistical support and strategies to find biostatistical mentoring. 4 videos1 reading1 assignment
|
5 modules
|
Intermediate level
|
5 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/biostatistics-study-design-and-analysis-for-grant-writing
| null |
752 |
Animals and Institutions
|
3,241
|
4.8
| 61 |
Leslie Irvine
|
University of Colorado Boulder
|
['Animal welfare', 'Sociological concepts']
|
This course explores animals within the context of the functional relationships that sociologists call “institutions.” We first examine the use of animals in laboratory science. We then examine the controversial transformation of animals into “livestock” and "meat." We also explore the perspectives of people committed to rejecting the construction and use of animals as food. Next, we focus on some of the roles of animals in human entertainment with particular attention to dog fighting and zoos. Finally, we investigate animal health and welfare through the lens of dilemmas in veterinary medicine and decisions in animal shelters. In this module, you will gain familiarity with the issues that shape the use of animals in scientific research and underlie the controversy surrounding it. 4 videos1 reading1 assignment2 discussion prompts In this module, you will learn about the system through which animals are transformed into “livestock.” 3 videos1 discussion prompt In this module, you will investigate how animals are central to how humans spend their leisure time. 4 videos1 assignment1 discussion prompt In this module, you will examine the social worlds of veterinary medicine and animal sheltering. 4 videos1 reading1 peer review2 discussion prompts
|
4 modules
|
Beginner level
|
5 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/animals-institutions
| null |
753 |
Foundations of Purchasing: Principles and Practices
|
Enrollment number not found
|
4.9
| 11 |
Manish Gupta
|
Coursera Instructor Network
|
['Ethical Procurement Practices', 'Negotiation Skills']
|
Effective supply chain is crucial for businesses to ensure consistent supply of raw materials and continuation of its value creation. Dive deeper into the core of purchasing with this detailed course, designed to provide you with a foundational understanding of the key concepts, strategies, and practices. This course is aimed at empowering participants with the necessary skills to manage purchasing activities effectively, forge strong supplier relationships, and contribute significantly to their organization's competitiveness and profitability.
Through this course, learners will grasp the critical role of purchasing in organizational success and supply chain optimization, learn the principles of effective purchasing, supplier selection, and gain proficiency in negotiating, managing contracts, and ethical procurement practices. Effective supply chain is crucial for businesses to ensure consistent supply of raw materials and continuation of its value creation. Dive deeper into the core of purchasing with this detailed course, designed to provide you with a foundational understanding of the key concepts, strategies, and practices. This course is aimed at empowering participants with the necessary skills to manage purchasing activities effectively, forge strong supplier relationships, and contribute significantly to their organization's competitiveness and profitability. 11 videos4 readings1 assignment3 discussion prompts
|
1 module
|
Beginner level
|
1 hour to complete
|
https://www.coursera.org/learn/foundations-of-purchasing-principles-and-practices
| null |
754 |
Essentials of Corporate Finance Specialization
|
27,258
|
4.7
| 1,281 |
Sean Pinder
|
The University of Melbourne
|
['Financial Analysis', 'Corporate Finance', 'Financial Ratio', 'Balance Sheet']
|
You will gain a firm understanding of corporate finance, including accounting principles and financial analysis, how value is created by global markets, the choices firms face when making financial decisions and defining attitudes towards risk. The Specialization concludes with a Capstone project that allows you to apply the skills you've learned throughout the courses. In this course, participants will learn the foundations of accounting principles and financial analysis, develop an understanding of the links between these, and the measurement of value creation at the firm level. This is the first course in a four-course Specialization on the Essentials of Corporate Financial Analysis and Decision-Making, created in partnership between the University of Melbourne and Bank of New York Mellon (BNY Mellon). View the MOOC promotional video here: http://tinyurl.com/jeoa83t In this course, participants will learn about how different markets around the world can interact to create value for, and effectively manage the risk of, corporations and their stakeholders. This is part of a Specialization in corporate finance created in partnership between the University of Melbourne and Bank of New York Mellon (BNY Mellon). View the MOOC promotional video here: http://tinyurl.com/j7wyowo In this course, participants will learn about the key financial decisions modern corporations face, as well as the alternative methods that can be employed to optimize the value of the firm’s assets. This is part of a Specialization in corporate finance created in partnership between the University of Melbourne and Bank of New York Mellon (BNY Mellon). In this course, participants will develop an understanding of the intuitive foundations of asset and investment valuation, and how alternative valuation techniques may be used in practice. This is part of a Specialization in corporate finance created in partnership between the University of Melbourne and Bank of New York Mellon (BNY Mellon). View the MOOC promotional video here: http://tinyurl.com/h75pzt6 The Capstone Project is the final part of the Essentials of Corporate Financial Analysis and Decision-Making MOOC Specialization. The Capstone is designed to allow students to bring together the skills acquired and knowledge gained over the preceding four courses of the Specialization by taking on the role of a financial analyst tasked with advising a wealthy private client on a significant strategic investment in a large listed firm operating across the globe.
View the MOOC promotional video here: http://tinyurl.com/j9fqv25
|
5 course series
|
Intermediate level
|
2 months (at 10 hours a week)
|
https://www.coursera.org/specializations/learn-finance
| null |
755 |
Architecting and Installing the Apigee Hybrid API Platform
|
2,408
|
4.7
| 38 |
Google Cloud Training
|
Google Cloud
|
[]
|
This course introduces you to the fundamentals and practices used to install and manage Google Cloud's Apigee API Platform for hybrid cloud. Through a combination of lectures, a hands-on lab, and supplemental materials, you will learn how to install and operate the Apigee API Platform. Introduction to the fundamentals and installation course on Google Cloud’s Apigee hybrid API platform. 2 videos1 reading This module provides an introduction to Apigee services, and an overview of Google Cloud, Kubernetes and Anthos. 6 videos1 assignment This module discusses the Apigee hybrid achitecture, terminology and networking. 6 videos1 assignment This module discusses the Apigee hybrid installation process, and the tools used to manage and configure the hybrid runtime plane. 9 videos1 reading1 assignment1 app item
|
4 modules
|
Beginner level
|
6 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/fundamentals-installation-of-apigee-hybrid-api-platform
| null |
756 |
Chinese for HSK 3 PART I
|
33,765
|
4.8
| 623 |
CHEN LI
|
Peking University
|
[]
|
大家好！Hi, everyone, welcome to join our Chinese for HSK Level 3 course. This is CHEN Li and LU Yun, and we are very happy to meet you here! Chinese for HSK 3 is a 10-week course. It consists of two parts: Part I, which is a 6-week program, covers vocabulary and grammar delivered mainly through dialogues and passages; Part II takes 4 weeks to complete and the foci are exercises and testing strategies.
Chinese for HSK 3 aims at the third level of HSK. It is the counterpart of Level 3 of the Chinese Language Proficiency Scales for Speakers of Other Languages and the B1 Level of the Common European Framework of Reference for Languages.
Chinese for HSK 3 Part I includes:
30 video lectures with dialogue role plays by PKU students;
More than 300 new words on the basis of HSK 1 and HSK 2;
More than 60 new grammar points;
Review the words you have learnt in HSK 1 and HSK 2 courses.
New words and texts via audio;
Quizzes for each lesson and HSK test papers;
At the end of the course, you will be able to communicate in Chinese at a basic level in your daily, academic and professional lives. You can manage most communication in Chinese when travelling in China.
Specifically, you will master certain grammar knowledge containing fundamental sentence structure and usage like sentences with “把”, sentences with “被”(passive voice), comparative sentences and rhetorical questions. Moreover, you will master the meaning of fixed structure and usage of sentences like “….for sb…”(对…来说), “increasingly…” (越来越), etc.
It does not matter if you complete HSK Level 1-2 or not, as long as you have obtained basic Chinese language competency. Hope you enjoy our Part I course and glad to see you in our next Part II course.
CHEN Li, LU Yun and Chinese for HSK Level 3 team. This week we will be learning expressions related to hobbies and interests. What's your favorite hobby? Do you know how to discuss your plan and travel place on weekends? At the end of this week, you will be able to answer the questions above in Chinese. You will learn 55 new words and 11 new grammar points this week. 5 videos10 readings13 assignments5 discussion prompts This week we will be learning expressions related to asking for sick leave, sending one's blessing or comfort others. What happened to you? Do you feel better? Do you know how to say" Don't be sad!"in Chinese? At the end of this week, you will be able to talk about these topics above in Chinese. You will learn 52 new words and 10 new grammar points this week. 5 videos10 readings13 assignments5 discussion prompts This week we will be learning expressions related to arrangements and plans. What programs do you want to watch? Will the bank open tomorrow? Do you know how to say "it is very convenient by subway"in Chinese? At the end of this week, you will be able to talk about these topics above in Chinese. You will learn 47 new words and 10 new grammar points this week. 5 videos10 readings13 assignments5 discussion prompts This week we will be learning expressions related to campus life and weather. Do you like online shopping? How to talk about exam,scores ,learning plans and learning experience? Are you used to extreme cold weather? At the end of this week, you will be able to talk about these topics above in Chinese. You will learn 52 new words and 10 new grammar points this week. 5 videos10 readings13 assignments5 discussion prompts This week we will be learning how to talk about describing someone's appearance and some kind of environment. Who do you look like? What kind of room would you like? What kind of place would you like to go? At the end of this week, you will be able to answer these questions above in Chinese. You will learn 56 new words and 12 new grammar points this week. 5 videos10 readings13 assignments5 discussion prompts This week we will be learning the usage and structure of “把”sentence, “被”sentence and "There be"sentence in Chinese. You will learn 41 new words and 12 new grammar points this week. 5 videos10 readings13 assignments5 discussion prompts 2 readings2 assignments
|
7 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/hsk-3
|
97%
|
757 |
Sustainable Development in the 21st Century with Ban Ki-moon
|
27,591
|
4.8
| 244 |
Ban Ki-moon
|
Yonsei University
|
[]
|
The course is designed for people that want to learn about the latest development agenda the international community agreed to achieve by 2030. Structured around the five pillars of Agenda 2030 – people, prosperity, planet, peace and justice, and partnership, students will learn that these pillars are interconnected and need to be integrated in practical policy-making and operational activities for development, in both developed and developing country settings. Following an introductory module on the main concepts of Agenda 2030 and the SDGs, successive modules will provide the foundation behind the SDGs for people, prosperity and planet, peace and partnership. A final module will explore the way forward and provide channels that the young generation can participate to integrate the SDGs in the policy-making of the students’ resident countries. To get a better idea of our course, we welcome you to take a look at our promotional video: https://www.youtube.com/watch?v=KATSb73TeB4 In this first module, you will be introduced to the overall concept and elements of the 2030 Sustainable Development Agenda. The 2030 Agenda for Sustainable Development has been an integral part of the global development agenda. The Sustainable Development Goals (SDGs) embraced the nature and characteristics of the Millennium Development Goals (MDGs) but produced a more comprehensive goal for all. We will breakdown the five key elements: People, Planet, Prosperity, Peace and Partnership. We will also examine each of the 17 Goals of the 2030 Sustainable Development Agenda. 11 videos6 readings1 assignment1 discussion prompt Within the SDGs, ending poverty remains a central objective of international development efforts. In Week 2, we will be looking at the concepts of poverty. The aim of this week is to examine different approaches to defining and measuring poverty and inequality and to understand the impact of global distribution of poverty. The causes and impacts of poverty such as unequal distribution of resources and power will also be discussed. Later, we will be looking at how the interrelationship between poverty and other issues, such as global health systems, hunger, gender equality and education will have an impact on the level of poverty. Furthermore, we will look into a specific case study of Bahrain’s health care reform. 13 videos8 readings1 assignment1 discussion prompt In Week 3, we will have a more detailed look at the scientific evidence that human activities are influencing the Earth at the planetary level. You will be introduced to the concepts of Anthropocene and Planetary Boundaries. The biosphere (all living organisms or “biodiversity”) is arguably just as – or more – important than climate for establishing the environmental conditions we enjoy on Earth, but receives much less attention. Furthermore, we will be examining the mitigation and adaptive options, on the local and global scales, in response to reduced environmental sustainability. Additionally, we will look at the international agreements for climate change and how they seek to meet the goals of the SDGs. Using current global environmental challenges, we will discuss ways in which communities and societies have utilized indigenous knowledge, scientific evaluations, technological innovations, societal regulations and laws, environmental monitoring, and policy prescriptions in environmental management at various scales. 10 videos7 readings1 assignment1 discussion prompt Where the last module focused on the activities within the 2030 Agenda to tackle the problems related to the Planet, this week will focus on the prosperity element of the 2030 Agenda for Sustainable Development. Economic development is a key component in any development agenda. You will be analyzing the past trends of economic and political development and will be introduced to examples of how to achieve sustainable economic development. We will touch upon concepts of sustainable economic trends such as social innovation and green jobs, buildings and energy sources. 8 videos5 readings1 assignment1 discussion prompt This week we will discuss the 16th Sustainable Development Goal to “Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels.” This week will cover the concepts of justice, inclusion, peace, global governance and global citizenship and the need for strong institutions. 11 videos8 readings1 assignment1 discussion prompt In this last module, we will look into the role of youth in the implementation of the SDGs. While the previous modules focused on the 5 “Ps” in the achievement of the SDGs, this module looks into the importance of tertiary education and the roles that universities play in mainstream education for sustainable development. This module also examines the empowerment and mobilizing of youth to become the enablers of the SDGs. 13 videos7 readings1 assignment1 discussion prompt 1 peer review
|
7 modules
|
Beginner level
| null |
https://www.coursera.org/learn/sustainable-development-ban-ki-moon
|
98%
|
758 |
Introduction to Financial Accounting
|
338,796
|
4.7
| 8,205 |
Brian J Bushee
|
University of Pennsylvania
|
['Financial Accounting', 'Accounting', 'Financial Statement', 'Balance Sheet']
|
Master the technical skills needed to analyze financial statements and disclosures for use in financial analysis, and learn how accounting standards and managerial incentives affect the financial reporting process. By the end of this course, you’ll be able to read the three most common financial statements: the income statement, balance sheet, and statement of cash flows. Then you can apply these skills to a real-world business challenge as part of the Wharton Business Foundations Specialization. To learn a foreign language like Accounting, you need quite a bit of practice in the basic foundations (grammar, syntax, idioms, etc.). This material is absolutely essential for being able to read and to understand books written in the language (in our case, financial statements.). This week, we will start building these foundations. We will start with an overview of financial reporting. What types of reports are required? Who makes the rules? Who enforces the rules? Then, we will cover the balance sheet equation and define/discuss Assets, Liabilities, and Stockholders' Equity. We will introduce debit-credit bookkeeping and do lots of practice in translating transactions into debits and credits. Finally, we will introduce a case of a start-up company to provide you insights into all of the steps necessary to go from recording the first transactions of a new business all the way through its first set of financial statements. 9 videos7 readings2 assignments We will start with a discussion of Accrual Accounting and how it affects the recognition of the Income Statement accounts: Revenues and Expenses. Then, we will cover adjusting entries, which are needed to prepare our internal books for the upcoming financial statements. Finally, we will discuss closing entries and the preparation of the Balance Sheet and Income Statement. At each stage, we will continue to work on the case of our start-up company. If you are not sick and tired of journal entries by the end of this week, then I have not done my job! 8 videos6 readings1 assignment Cash is King! We will start with the classification of cash flows into operating, investing, and financing activities. Then, we will work on preparing and analyzing the Statement of Cash Flows. We will wrap up the case on the start-up company by preparing and analyzing its Statement of Cash Flows. Finally, we will discuss the differences between Earnings, Cash from Operations, EBITDA, and Free Cash Flow. 7 videos4 readings1 assignment We will have our final exam this week. Because of the exam, I will cover Ratio Analysis, which will not involve any "new" material. While we will define and discuss a number of ratios, they will all basically involve dividing one accounting number by another. But, the analysis of what those ratios mean will involve a deep understanding of Balance Sheet and Income Statement accounts. Thus, the Ratio Analysis videos will help provide a nice review of the material, which will help you prepare for the exam. However, there will be no questions about ratio analysis on the exam. The only thing left to do after this exam is to impress your family, friends, and co-workers with your vast knowledge of Financial Accounting! 5 videos3 readings2 assignments
|
4 modules
| null |
13 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/wharton-accounting
|
96%
|
759 |
Advanced Concepts in Time Value of Money (TVM)
|
4,493
|
4.8
| 76 |
Gautam Kaul
|
University of Michigan
|
['Financial Analysis', 'Financial Planning (Business)', 'Time Value of Money (TVM)']
|
This course builds upon the fundamental concept of Time Value of Money (TVM) using more advanced applications and questions. You will apply the TVM concept in real-life problems of financial planning and saving for college. You will also learn more about loans and apply TVM concepts to borrowing and lending. You will realize that — while the applications are seemingly more complex, but when seen and broken-up into bite-size components — the framework, principles, and tools remain the same. After completing this course you will have an understanding of the detailed mechanics and reasoning behind any decision you make that has consequences for the future. The deeper exposure to financial transactions you will be applicable in any/all decisions. The great news is that these concepts and skills will transfer to your professional/business decisions.
This course is part of the four-course Foundational Finance for Strategic Decision Making Specialization. This week we will start this course with the first Mega Application that will expose us to more real-world situations confronted by us all. You are strongly encouraged to think through an application and draw timelines to realize that complex applications are a collection of the simpler ones we dealt with Course 1. As you work through the four Mega Applications in this course, look to find the common themes. In this application, we will start with a classic example of saving for a future need - to attend college. 3 videos4 readings This week's second Mega Example is about financial planning, agin something that can serve very useful because we typically work for some time and then want to maintain a standard of living. The key concepts here are again the same as those developed in the first course, but the issue is one of breaking down more difficult problems into bite-size pieces that resemble the simpler applications and assignments in Course 1. You are strongly encouraged to start attempting the Practice and Graded assignments - each has TEN questions with deliberate overlap with Course 1 and then some challenging scenarios in the later part of the assignments. 1 video2 readings2 assignments This week's Mega Application is my favorite because it shows you both the power of finance and its ability to simplify seemingly complex transactions. We all borrow and lend, though at different points in time, and even at the same time. This application is very detailed because it is meant to demonstrate the intuitive power of finance that makes calculations easy. 3 videos2 readings This is a Mega Application that will help you understand the power of simplicity in conducting financial examples. You are again encouraged to keep practicing and attempting the assignments. 1 video2 readings2 assignments
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4 modules
|
Intermediate level
|
14 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/time-value-of-money-two
| null |
760 |
Privacy in Europe
|
7,122
|
4.4
| 91 |
Jan Smits
|
EIT Digital
|
[]
|
Explore the intricacies of European privacy law in this focused course, designed as a follow-up to "Privacy in the Western World." This course places a strong focus on the European legal framework, which bases its privacy protection on seminal human rights treaties such as the UN Declaration on Human Rights. You'll gain insights into the historical context that shaped Europe's approach to privacy, beginning with economic cooperation initiatives set up to prevent another conflict after the devastating effects of World War II. As you progress, you'll learn how this cooperative framework expanded to address critical issues, including the paramount importance of respecting human rights and, increasingly, the protection of individual privacy—a subject that has attracted substantial global attention.
Dive into the legal elements that have played a key role in formalizing the notion of privacy and its legal protection. Specifically, you will examine the rules governing the exchange of personal data between the USA and Europe and delve into the foundational legal components that make up the General Data Protection Regulation (GDPR).
Upon completing this course, you'll have a thorough understanding of both the key legal elements and the historical context that led to the development of privacy protection in Europe.
Ready to expand your knowledge and become proficient in European privacy law? Enroll now to ensure you don't miss this opportunity. European privacy protection is based upon human rights treaties, both on a European level as well global level such as, e.g. the UN Declaration on Human Rights. First we deal with how the European cooperation came into being after the devastating effects of World War II. Economic cooperation was deemed necessary to prevent another war. From economic cooperation other issues became part of the negotiations, and to this day more and more policy fields have become part of the European cooperation. 6 videos7 readings1 assignment This European Legal system is based on ancient Roman Law and as such one of the oldest in the world. This module focuses on the privacy aspects of the European Legal System and explains some of its history, its first legislation on data protection and privacy and their link to human rights. Finally the enforcement institutes and their role are discussed. 7 videos11 readings1 assignment European privacy law was and continues to be shaped by rulings and judgements by national and European courts. We travel through the historically most impactful cases , trending from the human rights aspect towards the complete data protection nowadays. 8 videos10 readings1 assignment Nowadays privacy and data in Europe is protected by the General Data Protection Regulation (GDPR). All previous treaties, directives and regulations have led towards this regulation. As a result the GDPR is very comprehensive. This module will introduce the principles the regulation is based on and discuss most of its main elements. As one of the most progressive piece of legislation globablly it inspires other law makers to apply similar approaches in their legal system. The Californian State for example in 2020. 10 videos3 readings1 assignment One of the unique approaches the GDPR takes is the rights it gives individuals to protect their data. We shortly introduce each of them, providing you with the framework of the European privacy protection. 10 videos2 readings1 assignment This module is entirely dedicated to delve deeper in the subject of data protection and privacy. We provide you with additional reading material that will not be graded or required in the final examination. However we strongly advise you to scan or read through this module not only help you gain a better understanding of data protection law but also form a independent opinion on the subject. 7 readings The final quiz and opportunity for you to demonstrate that you mastered the content of this course. Good luck! 1 assignment
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7 modules
|
Intermediate level
|
18 hours to complete (3 weeks at 6 hours a week)
|
https://www.coursera.org/learn/privacy-eu
| null |
761 |
MERN Stack Front To Back: Full Stack React, Redux & Node.js Specialization
|
Enrollment number not found
|
Rating not found
| null |
Packt - Course Instructors
|
Packt
|
['MongoDB', 'Full-Stack Development', 'MERN stack', 'Node.js', 'React', 'full-stack development', 'Express', 'MERN Stack', 'MongoDB', 'Full-Stack Development', 'MERN stack', 'Node.js', 'React', 'full-stack development', 'Express', 'MERN Stack']
|
In this course, you'll embark on a complete journey through the MERN stack, mastering the intricacies of MongoDB, Express, React, and Node.js. You’ll learn to configure and connect to a MongoDB database, set up your server with Express, and build robust API routes. You’ll implement features like user authentication using JWTs and handle data validation. As you progress, the focus shifts to the frontend, where you'll dive into React for building dynamic user interfaces. You’ll learn how to manage state using Redux, create reusable components, and handle routing efficiently. This section will empower you to build sophisticated client-side applications that are both scalable and maintainable. Throughout the course, you'll integrate these concepts seamlessly to create a fully functional and interactive full-stack application. By the end of the course, you'll have a thorough understanding of deploying your application to production. From securing your keys to configuring Heroku, you’ll gain the skills needed to launch a polished, live web application.
This course is designed for developers with a basic understanding of JavaScript and web development who are looking to expand their skills in full-stack development. Familiarity with frontend frameworks like React and basic backend concepts is recommended but not required. Applied Learning Project Learners will build a complete, real-world eCommerce application, applying skills like user authentication, state management, and API integration to create a fully functional, secure web app. Projects focus on solving practical problems such as building dynamic product listings, handling user data securely, and deploying the app to a live environment. Configure and set up backend servers using Node.js and Express for efficient application management. Develop and secure API endpoints with JWT-based authentication to protect data. Connect and manage data using MongoDB and Mongoose, ensuring robust database interactions. Implement complex user profile features and validate data for accuracy and security. Create interactive user interfaces using React to enhance user experience. Manage complex application state effectively with Redux. Implement secure user authentication and perform form validations to ensure data integrity. Integrate frontend applications with backend APIs to enable seamless data communication. Create complex frontend applications utilizing advanced React techniques and best practices. Design dynamic user interfaces that handle complex state management effectively. Implement seamless data flow and integration with backend APIs. Evaluate and optimize React applications for deployment in production environments.
|
3 course series
|
Beginner level
|
1 month (at 10 hours a week)
|
https://www.coursera.org/specializations/packt-mern-stack-front-to-back-full-stack-react-redux-and-node-js
| null |
762 |
Introduction to Cloud Computing
|
352,590
|
4.6
| 6,660 |
Rav Ahuja
|
IBM
|
['Cloud Computing', 'Hybrid Multicloud', 'Devops', 'Iaas PaaS Saas', 'Cloud Native']
|
Start your cloud computing journey with this self-paced introductory course! Whether you need general cloud computing knowledge for school or business, or you are considering a career change, this beginner-friendly course is right for you. In this course you’ll learn about essential characteristics of cloud computing and emerging technologies supported by cloud. You’ll explore cloud service models, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Public, Private, and Hybrid deployment models.
Discover the offerings of prominent cloud service providers AWS, Google, IBM, Microsoft, and others, and review cloud computing case studies. Learn about cloud adoption, blockchain, analytics, and AI.
You will learn about the many components of cloud computing architecture including datacenters, availability zones, virtual machines, containers, and bare metal servers. You will also familiarize yourself with different types of cloud storage options, such as Object Storage.
You’ll gain foundational knowledge of emergent cloud trends and practices including Hybrid, Multicloud, Microservices, Serverless, DevOps, Cloud Native, Application Modernization, as well as learn about cloud security and monitoring. You’ll also explore cloud computing job roles and possible career paths and opportunities.
You will complete a number of labs and quizzes throughout this course to increase your understanding of course content. At the end of the course, you will complete a final project where you will deploy an application to Cloud using a serverless architecture, a valuable addition to your portfolio.
After this course, check out the related courses to help you towards your new career as a cloud engineer, full stack developer, DevOps engineer, cybersecurity analyst, and others. In Module 1, in the first lesson, you will learn the definition of cloud computing and its five essential characteristics. In the next topic, you will learn about the history and evolution of cloud computing and the benefits of the pay-as-you-go feature of cloud computing. The third topic will describe the key considerations, benefits, and challenges of cloud computing. You will next discuss some common cloud service providers. In the second lesson, you will learn the need for cloud adoption by businesses. You will then discuss some case studies of businesses that benefitted from cloud adoption. In the third lesson, you will learn about emerging technologies like IoT, AI, Blockchain, and so on that leverage cloud’s scalability and processing power to provide value to individuals and businesses alike, supported by some case studies. 12 videos7 readings4 assignments1 discussion prompt In Module 2, you will learn about the different types of service and deployment models of cloud computing. The first lesson covers the three main service models available on the cloud—Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS). You will learn the differences between each model, the advantages of each, and the key components of cloud infrastructure. The second lesson goes over the four main deployment models available on the cloud—public, private, hybrid, and community. You will learn what deployment models are and the differences and advantages of each model. At the end of the module, you will create an account on IBM Cloud. 8 videos5 readings3 assignments1 app item1 plugin In Module 3, you will learn about the various components of a cloud computing architecture, such as the virtualization of virtual machines and bare metal servers, and the difference between virtual machines and bare metal servers. You will learn the different types of virtual machines, how to build a secure cloud networking presence, how container-based technologies work, and the benefits of a Content Delivery Network. In the second lesson, we will also familiarize you with the four main types of cloud storage—Direct Attached, File, Block, and Object Storage. You will learn the differences in how they can be accessed, the capacity they offer, how much they cost, the types of data they are best suited to store, and their read-write speed. 14 videos3 readings3 assignments In Module 4, you will learn about the use cases and challenges of emergent trends in cloud computing, such as hybrid multi-cloud, serverless computing, and microservices. Additionally, this module will teach you about the core concepts and benefits of cloud native applications, the role of DevOps in addressing some of the complexities of cloud computing, and how organizations can benefit from modernizing their applications. 7 videos4 readings3 assignments In Module 5, you will learn about elements of cloud security, including Identity and Access Management and cloud encryption. This module will cover how organizations leverage cloud monitoring solutions to optimize business benefits. It will familiarize you with cloud adoption case studies in different industry verticals, and the various career opportunities and job roles available in the field of cloud computing today. 8 videos5 readings3 assignments In this module, you will complete a final project to deploy a containerized application on the cloud using a serverless technology (no programming experience needed). You can also demonstrate your knowledge of cloud computing by completing an optional assessment based on a cloud architecture design case study. 1 video3 readings1 assignment1 app item1 plugin
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/introduction-to-cloud
|
96%
|
763 |
Business Analysis: Key Definitions & Strategy Analysis
|
8,134
|
4.7
| 92 |
Igor Arkhipov
|
Starweaver
|
['Modeling', 'Risk', 'strategy', 'analysis', 'Change']
|
This comprehensive course provides a strong foundation in business analysis principles, techniques, and strategies. It covers essential topics such as the definition of business analysis, various requirement types, career paths in business analysis, and the Business Analysis Body of Knowledge (BABOK) guide. It also delves into key definitions and practical techniques used in business analysis. Additionally, the course focuses on strategic aspects, including analyzing the current state, defining future states, managing risks, and developing change strategies. Learners will gain hands-on experience through case studies and practical exercises, preparing them for success in the field of business analysis and beyond. This course is suitable for individuals aspiring to become business analysts, current junior business analysts looking to strengthen their skills, mid-career professionals seeking to transition into business analysis roles, and those preparing for business analysis certifications. It accommodates learners with varying levels of prior knowledge and experience in the field.
While no strict prerequisites are required, a basic understanding of business concepts and organizational operations can be advantageous. Familiarity with project management or experience in a business-related role is helpful but not mandatory. This course is structured to accommodate learners with varying levels of prior knowledge. In this introductory module, students will be familiarized with the course's content and the role of business analysis in organizations. They will learn about the career path of a Business Analyst and gain an overview of the Business Analysis Body of Knowledge. 6 videos2 readings1 assignment This module focuses on key definitions and concepts essential for a solid foundation in business analysis. It covers the Business Analysis Core Concept Model, concept modeling techniques, and the relationship between requirements and designs. 6 videos1 reading1 assignment This module delves into Strategy Analysis, a critical aspect of business analysis. Students will explore techniques such as analyzing the current state, using tools like the Business Model Canvas, SWOT analysis, and Business Process Analysis. They will also learn about bench marking, document analysis, and risk assessment. 37 videos3 readings3 assignments 1 assignment
|
4 modules
|
Intermediate level
|
6 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/business-analysis-mastery
| null |
764 |
Create and Lead an Ethical Data-Driven Organization
|
18,807
|
4.6
| 80 |
Aaron Hui
|
CertNexus
|
['Ethics Of Artificial Intelligence', 'policy', 'governance', 'Ethical Leadership', 'Code of Ethics']
|
Creating and leading an ethical data-driven organization, when done successfully, is a cultural transformation for an organization. Navigating a cultural shift requires leadership buy in, resourcing, training, and support through creation of boards, policies, and governance. Beyond leadership and organization, it is imperative to engage employees through forums and incentive programs for continual involvement. A strong understanding of ethical organizational policies provides the foundation for consistent monitoring to maintain an ethical culture. In this fifth course of the CertNexus Certified Ethical Emerging Technologist (CEET) professional certificate, learners will develop strategies to lead an applied ethics initiative, champion its crucial importance, and promote an ethical organizational culture. Learners will learn how to develop and implement ethical organizational policies and a code of ethics. They will also be prepared to evaluate the effectiveness of policies with internal and external stakeholders.
This course is the fifth of five courses within the Certified Ethical Emerging Technologist (CEET) professional certificate. The preceding courses are titled Promote the Ethical Use of Data-Driven Technologies, Turn Ethical Frameworks into Actionable Steps, Detect and Mitigate Ethical Risks, and Communicate Effectively about Ethical Challenges in Data-Driven Technologies. The first module in this course begins by outlining strategies for building ethics into the organization's culture. An ethical culture promotes ethical behavior in all areas of the business and encourages all internal stakeholders to engage in ethical behavior, regardless of department or individual roles and responsibilities. 13 videos3 readings1 assignment1 discussion prompt In this module, you'll explore some of the foremost ethical issues and principles that an organization must consider integrating into its governance and policies. Many of these considerations will be crucial to the process of building an ethical organization. 12 videos1 reading1 assignment1 discussion prompt In this module, you'll begin work on a code of ethics, an important building block for any organization that wishes to promote ethical behavior in the development of its data-driven technologies. You'll explore not only the creation of a code of ethics, but proper methods for deploying that code. 9 videos3 readings1 assignment1 discussion prompt Now that you've created an ethical organizational culture, evaluated key ethical considerations, and developed a code of ethics, you can begin working on the practical implementation of ethics in the form of policies. In this module, you'll develop and deploy policies that ensure your ethical vision is achieved and maintained. 14 videos2 readings1 assignment1 discussion prompt You'll work on one or more projects in which you'll apply your knowledge of the material in this course to practical scenarios. 2 peer reviews
|
5 modules
|
Beginner level
|
12 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/ethical-data-driven-technology-leader
| null |
765 |
Zn and Ni Based Batteries
|
1,636
|
4.5
| 11 |
Arunachala Nadar Mada Kannan
|
Arizona State University
|
['battery management systems', 'battery charging', 'Electric Vehicles', 'battery types']
|
Zn and Ni based Batteries: This course focuses on identifying active materials, chemistry and manufacturing processes as they relate to Zn as well as Ni batteries Battery selection and sizing for various applications. 1 video2 readings Module 1 provides the characteristics of various Zn-based batteries comprising Zn-MnO2, Alkaline MnO2 and Zn-Air batteries. The major objective in this module is to learn about the anode and cathode reactions in both the primary and secondary batteries. In addition, the objective is also to bring out the recent major developments of rechargeable Zn-based batteries such as alkaline MnO2 and Zn-Air batteries. 11 videos1 assignment1 discussion prompt Module 2 provides the characteristics of Ni-Cd and Ni-MH batteries. The major objective in this module is to learn about the Ni, Cd and MH electrode active materials, electrochemical characteristics reactions in both the primary and secondary batteries. In addition, the objective is also to bring out the unique design aspects for making the Ni-Cd and Ni-MH batteries sealed. 10 videos1 assignment Module 3 provides the operation characteristics of lead acid batteries along with state of charge estimation. The major objective in this module is to learn about the Pb anode and PbO2 cathode reactions as well as lead acid battery performance. In addition, the objective is also to bring out the unique design features of sealed lead acid batteries for various applications. 11 videos1 reading1 assignment1 peer review
|
4 modules
|
Beginner level
|
7 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/zn-and-ni-based-batteries
| null |
766 |
Creating New BigQuery Datasets and Visualizing Insights
|
26,378
|
4.6
| 1,740 |
Google Cloud Training
|
Google Cloud
|
[]
|
This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you.
After completing this course, enroll in the Achieving Advanced Insights with BigQuery course. Overview of what you will learn in this course 2 videos Create new permanent and temporary tables from your query results 6 videos1 assignment1 app item Load and create new datasets inside BigQuery 2 videos1 reading1 assignment2 app items Understand the differences between SQL JOINs and UNIONs and when to use each 7 videos1 assignment2 app items Create dashboards and visualizations with Looker Studio 5 videos1 assignment1 app item Summary of the course ley learning points 1 video
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/gcp-creating-bigquery-datasets-visualizing-insights
|
91%
|
767 |
AWS CloudTrail Getting Started
|
Enrollment number not found
|
Rating not found
| 1 |
AWS Instructor
|
Amazon Web Services
|
[]
|
With AWS CloudTrail, you can keep a record of when activity occurs in your AWS account. That activity is recorded in a CloudTrail event. In this course, you will learn the benefits and technical concepts of CloudTrail. CloudTrail is an Amazon Web Services (AWS) service offering that helps you with enabling operational and risk auditing, governance, and compliance of your AWS account. Using CloudTrail, you can view, search, download, archive, analyze, and respond to account activity across your AWS infrastructure. CloudTrail helps identify who or what took which action, which resources were acted on, and when the event occurred. It also helps identify other details to help you analyze and respond to activity in your AWS account. With AWS CloudTrail, you can keep a record of when activity occurs in your AWS account. That activity is recorded in a CloudTrail event.
In this course, you will learn the benefits and technical concepts of CloudTrail. CloudTrail is an Amazon Web Services (AWS) service offering that helps you with enabling operational and risk auditing, governance, and compliance of your AWS account. Using CloudTrail, you can view, search, download, archive, analyze, and respond to account activity across your AWS infrastructure. CloudTrail helps identify who or what took which action, which resources were acted on, and when the event occurred. It also helps identify other details to help you analyze and respond to activity in your AWS account. 1 reading1 assignment
|
1 module
|
Beginner level
|
1 hour to complete
|
https://www.coursera.org/learn/aws-trails-for-aws-cloudtrail-getting-started
| null |
768 |
The Talmud: A Methodological Introduction
|
18,668
|
4.6
| 286 |
Barry Scott Wimpfheimer
|
Northwestern University
|
[]
|
The Talmud is one of the richest and most complicated works of literature the world has ever known. Since being composed around 1500 years ago it has inspired not only religious reverence but significant intellectual engagement. In this course learners will be introduced to the unique characteristics of this text and the challenges that inhere in studying it while studying a chapter of the Talmud. Students of the course can expect to develop an appreciation for how the Talmud works and why it continues to inspire religious and intellectual devotion. They will be challenged to employ critical reading skills and to analyze legal and historical concepts. The Talmud is a canonical work of Jewish literature that collects the ideas and arguments of rabbis who lived between the first and eighth centuries CE. This module explains the basics of how the Talmud was composed, why the Talmud matters and how it is accessed today. 5 videos9 readings1 assignment The Talmud relies heavily on the authority and substance of its canonical predecessor, the Hebrew Bible. This module charts a trajectory from the biblical origins of the treatment of false testimony in Deuteronomy through its treatment within the second temple apocryphal book Susannah and the early Rabbinic law code, the Mishnah. 4 videos5 readings1 assignment Interpretation is a major component of Rabbinic literature and the Talmud. This module introduces the specific features of Rabbinic interpretation of the Hebrew Bible—its assumptions and its reading tools. 3 videos4 readings1 assignment Textual Criticism is a form of reading that looks to explain the meaning of a text by figuring out aspects of its composition history. This module will show how Talmudic passages are typically constructed and what scholars can do to figure out the original meaning of a text. 3 videos4 readings1 assignment The historical range of the different centuries of rabbinic literature makes it possible to take note of changes in the ways the different rabbis thought about the Bible and law. This module will demonstrate how later rabbis have a more abstract way of thinking about law while simultaneously having a more restrictive way of reading the Bible. 3 videos3 readings1 assignment Rabbinic literature consists of multiple works in three genres—Midrash, Mishnah and Talmud. This module introduces each of these different genres with a comparative analysis of texts related to false testimony in works of each type. 4 videos5 readings1 assignment The Talmud contains many stories that feature historical figures from the rabbinic period. In this module we will demonstrate the difficulty of reading these stories as history and model the use of literary tools for reading such materials. 3 videos4 readings1 assignment While some of the material we have studied is unsettling, we need to bear in mind that much of it is rabbinic idealization or fantasy. This module goes through both the fantasy of rabbinic power and the realities of the importance of the Talmud in the post-Talmudic age. 3 videos3 readings1 assignment
|
8 modules
| null |
14 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/the-talmud
|
97%
|
769 |
Effective Problem-Solving and Decision-Making
|
264,177
|
4.6
| 7,073 |
Diane Spiegel
|
University of California, Irvine
|
['Critical Thinking', 'Decision Theory', 'Decision-Making', 'Problem Solving', 'analysis']
|
Problem-solving and effective decision-making are essential skills in today’s fast-paced and ever-changing workplace. Both require a systematic yet creative approach to address today’s business concerns. This course will teach an overarching process of how to identify problems to generate potential solutions and how to apply decision-making styles in order to implement and assess those solutions. Through this process, you will gain confidence in assessing problems accurately, selecting the appropriate decision-making approaches for the situation at hand, making team decisions, and measuring the success of the solution’s implementation. Using case studies and situations encountered by class members, you will explore proven, successful problem-solving and decision-making models and methods that can be readily transferred to workplace projects. Upon completing this course, you will be able to:
1. Identify key terms, styles, and approaches to effective problem-solving and decision-making
2. Explain both the affordances and limitations associated with problem-solving and decision-making
3. Reflect on how mindset and personal bias influence your ability to solve problems and make decisions
4. Explain and discuss how organizational decisions or non-decisions impact personal development, team dynamics, and company-wide performance
5. Articulate how both good and bad team decisions can benefit your professional growth Problem-solving is an essential skill in today's fast-paced and ever-changing workplace. It requires a systematic approach that incorporates effective decision-making. Throughout this course, we will learn an overarching process of identifying problems to generate potential solutions, then apply decision-making styles in order to implement and assess those solutions. In this module, we will learn to identify problems by using a root cause approach as a foundational tool. Additionally, we will address problem parameters that often occur in business situations. Throughout this course, we will utilize a case scenario that will provide specific examples to illustrate the steps in the problem-solving and decision-making process. 1 video7 readings1 assignment1 discussion prompt In the previous module, we learned how to identify the root cause of a problem. Now we will discuss how mindset and personal bias can potentially limit creativity in solving workplace challenges. We’ll review problem-solving styles and creativity enhancement approaches to generate a variety of unique solutions while addressing constraints and limited resources. 1 video6 readings1 assignment1 discussion prompt In the previous module, we learned how to generate a variety of creative solutions. Now we need to decide which solution is the best option. We will explore which decision-making styles lend themselves to best solve the problem given its affordances and limitations. Tips for making better decisions are outlined as well as hazards to avoid. 1 video5 readings1 assignment1 discussion prompt In the previous module, we learned how to make the decision given the best information at hand. Once the decision is made, it’s time to implement and assess the chosen solution. As we get ready to implement, we are well-served to review situational variables as elements in the environment may have shifted during the decision-making process. We will also need to define the solution’s performance metrics and Key Performance Indicators (KPIs) in order to later measure or assess the solution’s impact on the organization. Anecdotal data is equally valuable as it can share the emotional impact on employees. 1 video5 readings1 assignment1 discussion prompt
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/problem-solving
|
97%
|
770 |
Influencing People
|
226,112
|
4.8
| 3,991 |
Maxim Sytch, Ph.D.
|
University of Michigan
|
['Leadership', 'Management', 'Social Skills', 'Influencer Marketing']
|
This course will improve your ability to influence people in situations where you cannot use formal authority. You will learn about effective ways to build, develop, and sustain a power base in your organization. You will also learn influence tactics that enable you to be more persuasive and influential in working with your superiors, peers, and even subordinates. In addition, you will learn how to build and maintain high-quality relationships to further maximize your informal power and ability to influence others. Importantly, you will distinguish between influence and manipulation and learn how to protect yourself from the unwanted influence of others. The influence strategies you learn in this course will make you a more confident and influential leader, presenter, and decision-maker. You will more effective in pitching business ideas to your superiors, influencing customers, and building coalitions across stakeholders. This course will not only give you strategic guidance on how to develop and maintain your network for influence and power, but we will also equip you with specific tactics and strategies that are proven to work for gaining power and influencing people. To lead effectively, you must have power. Your power can be formally defined, for example your position or job title. Your power can be informal, for example your expertise or charisma give you power that enable you to influence others. In this module, we will explore the meaning of power and where it comes from, helping you identify your bases of power and opportunities to increase you power over time. 14 videos5 readings1 assignment In this module, you will acquire a rich arsenal of influence tactics that will help you change people’s viewpoints and behaviors. These influence tactics will enable you to influence up in organizations (e.g., when you have to influence your boss) and laterally, such as when you have to influence your peers. More generally, these tactics will allow you to execute effectively in those situations when you either do not have or cannot rely on formal rank and formal power. 9 videos7 readings1 assignment1 peer review In addition to acquiring a tactical portfolio of influence tools that can be applied in group and individual meetings, effective leaders devote a lot of time to building and maintaining social relationships with various stakeholders. In this module, you will learn how build and maintain social relationships in order to maximize your informal power and influence in organizations. 10 videos2 readings1 assignment As a leader, people will try to influence you to make a particular decision or take a particular course of action. It is essential you are able to protect yourself from the unwanted influence of others, especially when those others might be attempting to manipulate you in ways that are not in the best interest of your team or organization. In this module, you will learn specific strategies and tactics that you can use to protect yourself and your team from the unwanted influence of others. 8 videos3 readings1 assignment1 peer review
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/influencing-people
|
97%
|
771 |
MaaS: Adoption and Use
|
Enrollment number not found
|
Rating not found
| null |
Soora Rasouli
|
Eindhoven University of Technology
|
[]
|
In this course you will learn how to evaluate the potential of MaaS for a city of country before putting substantial investment in realizing any MaaS pilots or large scale projects. More precisely, you will be introduced to methods allowing you to collect data from citizens. We will also have a look at some example studies in which this type of data has been analyzed to provide answers to the following questions: "Would a MaaS service attract enough travelers in the study area?"
"What would be the best service design to maximize MaaS adoption rates?"
"Would MaaS be really be a sustainable alternative; in other words: will it trigger more citizens to move towards more environmentally friendly transpotation options?" 8 readings5 assignments
|
1 module
|
Beginner level
|
1 hour to complete
|
https://www.coursera.org/learn/maas-adoption-and-use
| null |
772 |
Building and Managing Superior Skills
|
33,306
|
4.6
| 149 |
Dr. Valeri Chukhlomin
|
The State University of New York
|
['Self-Assessment', 'Skills Management', 'Self-Coaching', 'assessment', 'Generative AI awareness']
|
Designed with the modern professional in mind, our skills management course is your transformative journey towards career success. This course offers key insights into strategies for skills-based hiring, enabling you to identify and analyze job-specific skills in your chosen field. You'll establish a systematic process for auditing and advancing your skills, boosting your professional agility. Throughout this course, you'll become familiar with Generative AI as a forward-thinking tool for skills assessment, self-assessment, and development. This understanding will place you at the forefront of your profession, ready to embrace and navigate the rapidly evolving world of AI in skills management. Diving deeper, we unpack the principles of valid and reliable skills assessment, familiarizing you with essential standards and benchmarks. You'll master techniques for assessing skill acquisition and form a robust process for gathering the necessary tools and techniques. Here, we explore the potential of Generative AI, an emerging technology that could further refine these assessment techniques. Then, emphasizing self-awareness, the course guides you to effectively self-assess your job-specific skills, reinforcing your assessments with peer and expert feedback. You'll learn to estimate your total skillset score for specific skill sets, creating a foundation for career advancement. At this stage, we discuss how Generative AI could potentially enhance the accuracy of self-assessments in the future.
In the final stages, we discuss planning and executing skill-building training interventions using SMART goals. You'll use innovative tools such as Your Present Job Market Value, Self-Assessment Grid for Skills Evaluation (SAGE), and T-portfolio. The potential of Generative AI to improve these processes is also considered, positioning you at the cutting edge of your professional journey.
Upon completion of this course, you'll be equipped with the knowledge, tools, and innovative thinking necessary to optimize your skill-building journey and achieve career growth and advancement. With our course, you're not just taking a step forward; you're launching into a brighter, AI-augmented future.
Upon completion of this course, you will be able to:
• Identify and analyze job-specific skills in your area of interest.
• Develop a systematic process for analyzing and auditing your skills.
• Discover standards and benchmarks for assessing mastery of skill acquisition.
• Develop a process for gathering tools and techniques for skills assessment.
• Self-assess your mastery in job-specific skills, verified using peer/expert feedback.
• Estimate your total skillset score for job-specific skill sets.
• Plan and execute a skill-building training intervention using SMART skill-building goals.
• Understand the potential use of Generative AI in skills assessment, self-assessment, and development and remain at the forefront of your professional journey by being informed about emerging technologies.
This course is an invaluable stepping-stone towards your career growth and advancement, giving you the tools, insights, and innovative thinking needed to optimize your skill-building journey. The first lesson, "Specialization at a Glance," walks you through all stages of career self-management training and certification, giving you a bird's-eye view of the specialization. If you've already taken other courses in the specialization, you can either skip this lesson or skim through it quickly to refresh your memory. The second lesson provides an overview of the current Course 2 " Building and Managing Superior Skills." You will also begin working in your Career Development / Skills Management Lab. The latest addition to the lab activities is ChatGPT and other generative AI. In the third lesson, we describe our approach to skill development through self-quantification in a simulated, yet realistic job market scenario. 10 videos9 readings6 assignments1 discussion prompt Job applicants frequently overestimate their qualifications for the desired position, according to research. Module 2 focuses on evidence-based, data-driven methods and techniques for assessing skills from the standpoint of subject matter experts. Professionals use a variety of tools and techniques to assess competency, including rubrics, frameworks, standards, and benchmarks. Dr. Michele Forte, Associate Professor at SUNY Empire State University, will introduce these methods this week. Then, we'll talk about and start using specific tools for skill assessment in CDL workouts, followed by a discussion about using Generative AI tools for skill assessment. 10 videos2 readings5 assignments1 peer review1 discussion prompt You will learn how to choose and use appropriate assessment tools to conduct a thorough, accurate, evidence-based, and data-driven self-assessment of your transferable skills. This week's guest lecturer, Dr. Kymn Harvin (Rutigliano), Associate Professor at SUNY Empire State University, will walk you through these topics. Then, you will participate in CDL workouts aimed at honing your skills and increasing your marketability by using specific instruments. We will continue the discussion about the use of Generative AI tools for skill assessment, self-assessment, and development, as we did in previous modules. 11 videos6 readings5 assignments1 discussion prompt This Module will prepare you for ongoing skill-building and skills management. We anticipate that you will continue to develop your critical competency profile after completing this course. To that end, we recommend that you review your skills portfolio on a regular basis, perhaps once a month or as needed, and prepare for a self-directed training intervention. You are now well-versed in theoretical knowledge of skills assessment and self-assessment, as well as how to use SAGE ("The Self-Assessment Grid for Evaluation") and other instruments. You can also use ChatGPT and other generative AI tools. This week's exercises will assist you in self-organization. Dr. John Beckem, Associate Professor at SUNY Empire State University, is the guest speaker for this Module. 12 videos9 readings5 assignments1 peer review1 discussion prompt
|
4 modules
|
Intermediate level
| null |
https://www.coursera.org/learn/career-brand-development-self-coaching
|
98%
|
773 |
Recording in Journals & Posting in Ledgers
|
7,366
|
4.8
| 144 |
Andrea Eliassen
|
University of California, Irvine
|
[]
|
This course covers the basic procedures involved in recording financial entries in Journals and Ledgers. Upon completing this course, you will be able to analyze and record various business transactions. You will also learn about the accounting cycle, posting transactions, accrual accounting, and cash accounting. You will also have the opportunity to practice these skills through a series of activities that provide real world experience. In this module we will review the process of recording proper entries into the general journal. We will start by walking through the step-by-step process of analyzing and recording service business transactions that follow the debit and credit rules. You will then have the opportunity to record transactions in the general journal on your own in this module's graded activity. 3 videos2 readings2 assignments In this module we will review the process of posting transactions from the general journal to the ledger. We will start by introducing ledger forms and T-accounts, then we will proceed to a walkthrough of the proper steps of posting transactions. You will then have the opportunity to post transactions from the general journal to the ledger on your own in this module's graded activity. 3 videos2 readings2 assignments In this module we will introduce the trial balance and the process of correcting entries. We will begin with an overview of how to transfer data from the ledgers to the trial balance, and continue with a step-by-step walkthrough of correcting entries. You will then have the opportunity to prepare your own trial balance in this module's graded activity. 3 videos2 readings2 assignments In this module we will introduce and learn to differentiate between cash accounting and accrual accounting. We will begin by reviewing key concepts related to accrual accounting including the periodicity assumption, the expense recognition principle, the revenue recognition principle, and the matching principle. You will then have the opportunity to work through example problems on your own in this module's activity. 3 videos2 readings2 assignments
|
4 modules
| null |
10 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/recording-business-transactions
| null |
774 |
Clinical Trials Operations Specialization
|
15,521
|
4.7
| 390 |
David M. Shade, JD
|
Johns Hopkins University
|
['Data Collection', 'Trial Design', 'Data Management', 'Clinical Data Management', 'Ethics', 'Data Collection', 'Trial Design', 'Data Management', 'Clinical Data Management', 'Ethics']
|
This specialization is designed for individuals and teams that will be running or interacting with clinical trials. In four courses, learners will develop insights and build the skills they need to design, manage, and monitor clinical trials as well as analyze, document, and communicate the results. Learners will also learn best practices regarding ethics, safety, participant recruitment, regulatory compliance, and reporting standards. The core principles and skills of the specialization will lay the foundation for a successful career in the field. Applied Learning Project Learners will demonstrate their mastery of skills, including trial design, data collection and management, statistical monitoring, trial ethics, participant recruitment and retention, data analysis, communication of results, and advanced operational techniques. Evaluate and select clinical trial designs Implement bias control measures Randomize participants into groups Define clinical trial outcomes Collect and manage clinical trials data Assemble and share clinical trials data Conduct statistical performance monitoring Perform quality assurance for clinical trials Detect and respond to protocol events Recognize and respond to misconduct Safeguard participant safety and trial integrity Develop and maintain study documents Calculate clinical trial sample size Monitor clinical trial performance Analyze results from clinical trials Communicate results from clinical trials
|
4 course series
|
Beginner level
|
4 months (at 3 hours a week)
|
https://www.coursera.org/specializations/clinical-trials-operations
| null |
775 |
Introduction to Financial Engineering and Risk Management
|
40,115
|
4.6
| 234 |
Garud Iyengar
|
Columbia University
|
['Binomial Distribution', 'Fixed Income', 'black scholes model', 'Swaps and options', 'Derivatives']
|
Introduction to Financial Engineering and Risk Management course belongs to the Financial Engineering and Risk Management Specialization and it provides a fundamental introduction to fixed income securities, derivatives and the respective pricing models. The first module gives an overview of the prerequisite concepts and rules in probability and optimization. This will prepare learners with the mathematical fundamentals for the course. The second module includes concepts around fixed income securities and their derivative instruments. We will introduce present value (PV) computation on fixed income securities in an arbitrage free setting, followed by a brief discussion on term structure of interest rates. In the third module, learners will engage with swaps and options, and price them using the 1-period Binomial Model. The final module focuses on option pricing in a multi-period setting, using the Binomial and the Black-Scholes Models. Subsequently, the multi-period Binomial Model will be illustrated using American Options, Futures, Forwards and assets with dividends. Welcome to Financial Engineering and Risk Management 1 video3 readings Welcome to Week 2! This week, we will cover mathematical foundations that are necessary for the study of future modules. In a nutshell, we will introduce probabilities and optimization. The theory of probability is the mathematical language to characterize uncertainties, e.g. how to describe the chances that the price of a particular stock will go up tomorrow. To make things precise, we need probabilities. Optimization is a set of toolkits that allow us to search for optimal solutions. For example, given a budget constraint, how do we maximize the profit? We need mathematical optimization. Financial engineers apply probabilistic models to capture the regularities of financial products, and apply optimization techniques to optimize their strategies. These mathematical toolkits will serve as a cornerstone for your financial engineering career. 18 videos6 readings5 assignments Welcome to Week 3! This week, we officially embark on the journey of financial engineering and risk management. We will start with the fundamentals of financial engineering, i.e. the principles of pricing. In financial markets, given a financial product, how do we calculate its prices? These pricing principles will serve as the cornerstone of our future modules. We will also cover the basics of fixed income instruments, which serve as the building blocks of financial markets. If you get stuck on the quizzes, you should post on the Discussions to ask for help. (And if you finish early, I hope you'll go there to help your fellow classmates as well.) 7 videos2 readings3 assignments Welcome to Week 4! This week, we will cover a new family of financial products: derivative securities. Derivative securities, as the name suggests, are financial products that derive their value from some underlying assets, such as interest rates or stocks. The prosperity of modern financial markets is due in large part to the wide variety of derivative securities on the markets such as forwards, futures, swaps, and options as we will introduce in this module. We will also introduce the 1-period binomial model, a simplified framework that allows us to calculate the prices of derivative securities. Despite its simplicity, 1-period binomial model is the building block of more powerful pricing models as we will find out in future modules. As always, if you get stuck on the quizzes, you should post on the Discussions to ask for help. (And if you finish early, I hope you'll go there to help your fellow classmates as well.) 11 videos3 readings4 assignments Welcome to Week 5! This week, we will continue from the last module, and extend from the 1-period binomial model to the multi-period binomial model. Multi-period binomial model is nothing but stacking multiple 1-period binomial models together. We will see how this simple construction allows us to price financial products over long horizons. As an illustrative example, we will price the American options using the multi-period model. Moreover, we will cover more advanced pricing models such as the Black Scholes model. We will see how the Black Scholes model is a natural extension of the multi-period binomial model and is widely applicable in practice. As always, if you get stuck on the quizzes, you should post on the Discussions to ask for help. (And if you finish early, I hope you'll go there to help your fellow classmates as well.) 10 videos7 readings5 assignments1 discussion prompt
|
5 modules
|
Intermediate level
|
19 hours to complete (3 weeks at 6 hours a week)
|
https://www.coursera.org/learn/financial-engineering-intro
| null |
776 |
Introduction to Generative AI
|
393,045
|
4.7
| 5,505 |
Google Cloud Training
|
Google Cloud
|
[]
|
This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps. This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps. 1 video1 reading1 assignment
|
1 module
|
Beginner level
| null |
https://www.coursera.org/learn/introduction-to-generative-ai
|
98%
|
777 |
Specialized Models: Time Series and Survival Analysis
|
15,729
|
4.5
| 126 |
Mark J Grover
|
IBM
|
['Cluster Analysis', 'Dimensionality Reduction', 'Unsupervised Learning', 'Time Series', 'K Means Clustering']
|
This course introduces you to additional topics in Machine Learning that complement essential tasks, including forecasting and analyzing censored data. You will learn how to find analyze data with a time component and censored data that needs outcome inference. You will learn a few techniques for Time Series Analysis and Survival Analysis. The hands-on section of this course focuses on using best practices and verifying assumptions derived from Statistical Learning. By the end of this course you should be able to:
Identify common modeling challenges with time series data
Explain how to decompose Time Series data: trend, seasonality, and residuals
Explain how autoregressive, moving average, and ARIMA models work
Understand how to select and implement various Time Series models
Describe hazard and survival modeling approaches
Identify types of problems suitable for survival analysis
Who should take this course?
This course targets aspiring data scientists interested in acquiring hands-on experience with Time Series Analysis and Survival Analysis.
What skills should you have?
To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Supervised Machine Learning, Unsupervised Machine Learning, Probability, and Statistics. This module introduces the concept of forecasting and why Time Series Analysis is best suited for forecasting, compared to other regression models you might already know. You will learn the main components of a Time Series and how to use decomposition models to make accurate time series models. 10 videos3 readings3 assignments This module introduces you to the concepts of stationarity and Time Series smoothing. Having a Time Series that is stationary is easy to model. You will learn how to identify and solve non-stationarity. Smoothing is relevant to you as it will help improve the accuracy of your models. 13 videos3 readings3 assignments This module introduces moving average models, which are the main pillar of Time Series analysis. You will first learn the theory behind Autoregressive Models and gain some practice coding ARMA models. Then you will extend your knowledge to use SARMA and SARIMA models as well. 9 videos3 readings3 assignments This module introduces two additional tools for forecasting: Deep Learning and Survival Analysis. In addition to AI and Machine Learning applications, Deep Learning is also used for forecasting. Survival Analysis is a branch of Statistics first ideated to analyze hazard functions and the expected time for an event such as mechanical failure or death to happen. Survival Analysis is still used widely in the pharmaceutical industry and also in other business scenarios with limited data related to censoring, the lack of information on whether an event occurred or not for a certain observation. 8 videos3 readings3 assignments1 peer review
|
4 modules
|
Intermediate level
|
11 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/time-series-survival-analysis
| null |
778 |
After the Arab Spring – Democratic Aspirations and State Failure
|
16,774
|
4.7
| 529 |
Dr. Ebrahim Afsah
|
University of Copenhagen
|
[]
|
Learn why the hope and excitement of the Arab Spring is gone, why so many Arab states are falling apart, why the youth are so frustrated, why there are so many refugees, and what can be done about it. The so-called Arab Spring appeared to end decades of exceptionalism and bring the Arab world back into the mainstream of global developments. The rebellions promised the return of politics and the reassertion of popular sovereignty against their corrupt and geriatric leaders. Much hope and flowery language greeted the young men and women who deposed their leaders and tried to build new, better societies.
Today, the Arab world is in deep crisis. Of the 22 member states of the Arab League, at least five have essentially collapsed: Iraq, Libya, Yemen, Somalia and Syria exist only in name today, as their territories have fallen to competing, murderous armed groups. In the remaining countries, the old autocracies have reasserted themselves. The repression at home is now worsened by regional conflict on an unprecedented scale, and the resulting frustration has led to the biggest refugee flows in recent memory. What went wrong?
This course offers an overview of the structural shortcomings of Arab states and societies, which help us understand why the democratic awakening did not happen but instead “has given way to civil wars, ethnic, sectarian and regional divisions and the reassertion of absolutism.” This raises the obvious and renewed question whether there is something inherent in the Arab, and by analogy Muslim, condition that makes them special. Does this condition make this part of the world impervious to generally observable trends towards greater accountability, popular participation in political decision-making, greater generation and fairer division of economic wealth? Join this course to find out! In this section, you will become acquainted with some of the mistakes that were made in the decades prior to the outbreak of the recent Arab rebellions. These shortcomings have led to stunted and underperforming political systems, much at variance with developments elsewhere. 4 videos1 reading4 assignments4 discussion prompts At the heart of most of the enduring problems plaguing the Arab world is the availability of essentially free income flowing to the governments of the region. These ‘rents’ have sustained a repressive arrangement in which citizens pay little or no taxes and have no voice. 4 videos1 reading4 assignments4 discussion prompts Social action inevitably produces institutions, namely values, stable, repeated patterns of behaviour. In this section, you will learn what institutions are, how they come about, how their relative effectiveness is measures, how and why they decline, and why all that matters. 4 videos1 reading4 assignments4 discussion prompts This section deals with the material bases of popular discontent, especially the connection between the states’ explicit promises of delivering welfare that have become increasingly unsustainable in the face of exploding population growth and falling revenues. 4 videos1 reading4 assignments4 discussion prompts Structural changes beyond anyone’s control lead to different ways of living and, thus, value changes. With explosive population growth, social institutions have not kept up and norms are contested, often violently. Arab education and research especially have underperformed. 4 videos1 reading4 assignments4 discussion prompts Tying together some of the structural shortcomings that have produced the dysfunction that drove the Arab rebellions, this section casts a somewhat gloomy picture about the formidable tasks ahead if these societies want to redress the causes of discontent and return to stability. 4 videos1 reading4 assignments4 discussion prompts
|
6 modules
|
Beginner level
| null |
https://www.coursera.org/learn/after-the-arab-spring
|
97%
|
779 |
Energy: The Enterprise
|
21,389
|
4.8
| 1,052 |
Martin Casstevens
|
University at Buffalo
|
[]
|
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. We will discuss the concept, scope and types of energy. We will explore energy's origins, uses, and evolving sources along with the properties and effects of greenhouses gases and their global warming potentials. 3 videos4 readings4 assignments We will discuss ultimate sources of energy and potential uses for certain sources of energy. We will review energy timelines and the economics involved with energy, along with stabilizing pricing. 4 videos3 readings4 assignments We will discuss innovations in energy as well as the movement and storage of energy along with supply and demand. 9 videos4 readings5 assignments We will focus on workforce opportunities and preparation for a future in energy fields. 5 videos3 readings3 assignments
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/energy-industry-overview
|
98%
|
780 |
Philosophy and the Sciences: Introduction to the Philosophy of Physical Sciences
|
41,012
|
4.7
| 919 |
Professor Michela Massimi
|
The University of Edinburgh
|
[]
|
What is the origin of our universe? What are dark matter and dark energy? This is the first part of the course 'Philosophy and the Sciences', dedicated to Philosophy of the Physical Sciences. Scientific research across the physical sciences has raised pressing questions for philosophers. The goal of this course is to introduce you to some of the main areas and topics at the key juncture between philosophy and the physical sciences.
Each week we will introduce you to some of these important questions at the forefront of scientific research.
We will explain the science behind each topic in a simple, non-technical way, while also addressing the philosophical and conceptual questions arising from it. We’ll consider questions about the origin and evolution of our universe, the nature of dark energy and dark matter and the role of anthropic reasoning in the explanation of our universe.
Learning Objectives
Gain a fairly well-rounded view on selected areas and topics at the intersection of philosophy and the sciences
Understand some key questions, and conceptual problems arising in the natural sciences.
Develop critical skills to evaluate and assess these problems.
Suggested Reading
To accompany 'Philosophy and the Sciences', we are pleased to announce a tie-in book from Routledge entitled 'Philosophy and the Sciences for Everyone'. This course companion to the 'Philosophy and the Sciences' course was written by the Edinburgh Philosophy and the Sciences team expressly with the needs of MOOC students in mind. 'Philosophy and the Sciences for Everyone' contains clear and user-friendly chapters, chapter summaries, glossary, study questions, suggestions for further reading and guides to online resources.
Please note, this companion book is optional - all the resources needed to complete the course are available freely and listed on the course site. Introduction to philosophy of science: the nature of scientific knowledge, the debates about the scientific method and the problem of underdetermination. 3 videos7 readings1 assignment1 discussion prompt How did our universe form and evolve? Was there really a Big Bang, and what came before it? 5 videos7 readings1 assignment1 discussion prompt According to the currently accepted model in cosmology, our universe is made up of 5% of ordinary matter, 25% cold dark matter, and 70% dark energy. But what kind of entities are dark matter and dark energy? 5 videos7 readings1 assignment1 discussion prompt Anthropic reasoning attempts to understand peculiarities of the physical universe via context-sensitive observers in a multiverse of different distinct universes. What are the problems and prospects of this view? 3 videos5 readings1 assignment1 peer review1 discussion prompt 2 readings
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5 modules
| null |
11 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/philosophy-physical-sciences
|
97%
|
781 |
eHealth: More than just an electronic record
|
22,789
|
4.6
| 321 |
Tim Shaw
|
The University of Sydney
|
[]
|
The MOOC, "eHealth: More than just an electronic record!", is multidisciplinary in nature, and aims to equip the global audience of health clinicians, students, managers, administrators, and researchers to reflect on the overall impact of eHealth on the integration of care. It explores the breadth of technology application, current and emerging trends, and showcases both local and international eHealth practice and research. The entire eHealth Course consists of 5 modules and takes about 5 weeks to complete. Completion certificates are issued on the basis of participation in all 5 modules. Completing the health practice assignment in Module 5 entitles you to advanced standing in some of the eHealth courses run by the Faculty of Health Sciences, University of Sydney.
What you'll learn
- The fundamentals of eHealth and where it is heading
- What kind of health data we are currently collecting and how it will transform healthcare in the future
- How new technologies are helping health consumers participate in their own healthcare
- How eHealth can improve the coordination and efficiency of healthcare and what the barriers might be
Length: Self-paced 5 week course
Study time commitment: 3 hours per week
Assessable components: Assignment 1 in Module 2 (40%) and Assignment 2 in Module 5 (60%).
Guest presenters (listed in alphabetical order):
* Jordan Andersen | The University of Sydney
* Dr Teresa Andersen | Sydney Local Health District
* Dr Robert Birnbaum | Harvard Medical School / Partners Healthcare
* Melissa Brunner | The University of Newcastle & The University of Sydney
* Professor Jane Burns | Young and Well Cooperative Research Centre & The University of Sydney
* Professor Rafael A. Calvo | The University of Sydney
* Dr Andrew Campbell | The University of Sydney
* Dr Jelle Demeestere | John Hunter Hospital, Newcastle NSW
* Professor Hugh Durrant-Whyte | The University of Sydney
* Karen Finnin | Physios Online
* Professor Afaf Girgis | UNSW Medicine
* Anna Janssen | The University of Sydney
* Professor Judy Kay | The University of Sydney
* Dr Melanie Keep | The University of Sydney
* A/Professor Jinman Kim | The University of Sydney
* Dr John Lambert | eHealth NSW
* Dr Melanie Keep | The University of Sydney
* Dr Karen Luxford | Clinical Excellence Committee NSW
* Michael Marthick | Chris O’Brien Lifehouse & The University of Sydney
* A/ Professor Mark McEntee | The University of Sydney
* Professor Kathryn Refshauge | The University of Sydney
* Dr Ursula Sansom-Daly | Sydney Children's Hospital, Prince of Wales Hospital & UNSW Medicine
* Dr Arran Schlosberg | The University of Sydney
* Professor Stephen Simpson | The University of Sydney
* Professor Leanne Togher | The University of Sydney
* Josh Zadro | The University of Sydney Key question: “What are the fundamentals of eHealth and where is it heading?” To complete this introductory module you will need to view the video lectures for each lesson and complete the four listed ungraded learning activities. It is also recommended that you sample the module reference and further resource list to consolidate your learning. 5 videos4 readings2 assignments1 discussion prompt "How are new technologies helping consumers 'participate' in healthcare?" To complete this module you will need to view the video lectures for each lesson and complete the two listed ungraded learning activities. You are also required to complete the graded Peer Review Assignment 1 (40%) for submission as per the assignment instructions. It is also recommended that you sample the module reference and further resource list to consolidate your learning. 9 videos3 readings1 assignment1 peer review2 discussion prompts "What kind of health data do we collect now and how will it transform healthcare in the future?" 10 videos3 readings1 assignment1 discussion prompt "How can eHealth improve the coordination and efficiency of healthcare and what are the barriers?" 8 videos3 readings2 assignments "How can eHealth principles and technologies be applied in my own professional practice?" 7 videos2 readings1 peer review
|
5 modules
| null |
12 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/ehealth
|
97%
|
782 |
Foundations of Data Analysis with Pandas and Python
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Enrollment number not found
|
Rating not found
| null |
Packt - Course Instructors
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Packt
|
['Data Analysis', 'Pandas DataFrames', 'Anaconda Setup', 'Python Crash Course', 'Python Programming']
|
Embark on a comprehensive journey into data analysis with Python and Pandas. Learn to set up Anaconda and Jupyter Lab on macOS and Windows, navigate Jupyter Lab's interface, and execute code cells. - You'll start by mastering essential Python programming concepts, including data types, operators, variables, functions, and classes.
- Then, dive into Pandas to create and manipulate Series and DataFrames. The course covers data importing from sources like CSV, Excel, and SQL databases, along with techniques for sorting, filtering, and data extraction.
- Advanced analysis methods, including group-by operations, merging, joining datasets, and pivot tables, are also explored to equip you with the skills for efficient and sophisticated data analysis.
Ideal for aspiring data analysts and scientists, no prior programming knowledge is necessary with the included Python crash course. In this module, we will guide you through the initial setup required for this course, including installing the Anaconda distribution on both macOS and Windows, and creating Python environments using Anaconda Navigator. You'll also learn to unpack the provided course materials, navigate the Jupyter Lab interface, execute code cells, and import necessary libraries to get you started on your data analysis journey. 8 videos2 readings1 assignment In this module, we will cover the essentials of Python programming, starting with the use of comments to enhance code readability. You'll gain familiarity with Python's basic data types, operators, variables, and built-in functions, laying the groundwork for effective coding. We will delve into custom functions, string methods, lists, indexing and slicing, dictionaries, and classes to build your programming skills. Finally, you will learn to navigate and use Python libraries within Jupyter Lab, a critical skill for data analysis. 12 videos1 assignment In this module, we will explore the creation and manipulation of Pandas Series objects from different data sources like lists and dictionaries. We will delve into essential methods and attributes of Series, understand the use of parameters and arguments, and learn techniques to import data into Series using 'pd.read_csv'. Additionally, we will cover methods for inspecting, sorting, and extracting Series values, along with advanced operations like broadcasting and applying functions to Series elements. 21 videos1 reading2 assignments
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3 modules
|
Beginner level
|
9 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/packt-foundations-of-data-analysis-with-pandas-and-python-hmwp9
| null |
783 |
Career 911: Your Future Job in Medicine and Healthcare
|
27,881
|
4.5
| 154 |
Dr. Melissa A. Simon
|
Northwestern University
|
[]
|
This course aims to help high school students, recent graduates, and those considering career transitions explore health care career options and learn strategies for entry into the health care workforce and health related fields. There are lots of amazing job opportunities in medicine and healthcare! Join us, as we share the strategies and secrets for getting those jobs. This course will introduce you to healthcare professions, help you map a path towards a health career, and impart skills relevant for any career, including: articulating your personal story, resume and cover letter writing, job search, interviewing, professional networking, and professional communications. In this course, you will hear the personal stories, experiences, and journeys of dozens of people who work in health related careers. You will also have the opportunity to connect with a supportive community of students, mentors, and health care professionals to explore your interests, find resources, and discover exciting new opportunities.
The course features more than 50 different guests and lecturers, including Northwestern University faculty from Feinberg School of Medicine; the Kellogg School of Management; the Medill School of Journalism, Media, Integrated Marketing Communications; the School of Professional Studies; Weinberg College of Arts and Sciences; and the School of Communication.
The course is also a resource and tool through which educators, parents, career counselors and others can support students’ career readiness and professional advancement. Careers where you can make a difference in people's lives 3 videos7 readings1 assignment1 peer review Healthcare professionals briefly describe what they do and introduce medical terminology 14 videos Personal stories & career journeys of health professionals and students 6 videos1 reading2 assignments1 peer review Packaging your personal story to increase your professional opportunities 2 videos1 reading2 assignments1 peer review How to use social networks - everyone you know - to find opportunities 1 video1 reading1 assignment1 peer review Nuts and bolts of resume writing 1 video1 reading3 assignments Nuts and bolts of a cover letter 1 video1 reading2 assignments1 peer review Communication skills and presence to stand out in an interview 1 video1 reading2 assignments1 peer review Additional Career 911 topics for success in entering a health career 10 videos1 reading2 assignments
|
9 modules
| null |
19 hours to complete (3 weeks at 6 hours a week)
|
https://www.coursera.org/learn/healthcarejobs
|
96%
|
784 |
Making Architecture
|
138,215
|
4.8
| 1,362 |
Nenad Katic
|
IE Business School
|
[]
|
Making architecture offers a unique insight into the mind and work of an Architect, starting with the basics of the profession and culminating with the production of a scaled site model. The course should act as ideal preparation for those interested in undertaking an undergraduate degree in Architecture, although its flexible, intriguing and enjoyable content makes it accessible for all those looking to increase their knowledge in the field. Delivered primarily by Professors from the IE School of Architecture and design in Segovia (Spain), the course begins by examining the mind-set of an Architect - asking how they think and what they do to train their creative minds, moving on to using inspiration from the environment to stimulate design ideas. Finally, the course concludes by looking at some of the more technical aspects of Architecture - such as composition, form, space and hierarchy - and stressing the importance of creating a story that helps define your design.
This fascinating content is delivered principally from the stunning design studio at the IE school of Architecture and features external videos from a few beautiful locations in the city of Segovia. Finally, it includes interviews from Pritzker Prize executive director - and Dean of the school of Architecture and design at IE - Martha Thorne, with a number of award winning practising architects such as Sarah Wigglesworth and Cristoph Ingenhoven. In this course, we're not just going to tell you what the architect does, we're going to show it to you. You're going to actually do, on a small scale, the work that an architect does.What the architect does is to have a certain vision about how things might be better. We're going to give you an introduction to that mindset and to that way of working. The study of architecture really engages all your skills. You learn how to work in teams, you learn how to communicate. You learn how to think critically and analytically. You develop all of your creative skills in the study of architecture. In this first module we are going to do three things. We're going to dispel some of the myths about what you need in order to be an architect. We're also going to talk about what an architect does and doesn't do. Then we're going to work on a short design exercise that begins to stretch your muscles to get you going on the design process. 15 videos1 peer review2 discussion prompts What we're going to do in this module is to discuss the work of architecture in a wider context. In this we will explore the relationship the architect has with the environment (both its material environment and its social environment. So, these kinds of questions, this ability to think about an object in its broader context is what we're going to develop. By the end of the module, you're going to be able to think about and map a building's broader context. The social and material context in which a project exists. 10 videos1 peer review3 discussion prompts In this module we are going to delve more into the technical side of architecture. We will explore essential principles such as: composition, hierarchy, balance, and space. Having learned how you interact with the environment, this is where you learn how to put your ideas into practice. You will learn what is necessary in order to ensure your structure connects with people living near it and interacting with it on a daily basis. Also, we will explore how architects use the natural and physical environment to stimulate their creative process - taking a look at incredible examples from renowned architects. Finally, you will receive tips on how to succeed in this week's assignment. 18 videos1 peer review1 discussion prompt In this module, we focus on developing the story behind your design. All great architects have great stories and we will give you an insight to some of those in this week. We will show you how you can develop your own story which will enable you to build the necessary emotional connection to your design. Also, we educate you in how to use photography and modern tools like instagram in order to make your design look as attractive as possible to a wider audience. Finally, we will prepare you for your final and most important assignment of the course. 12 videos1 peer review2 discussion prompts
|
4 modules
|
Beginner level
| null |
https://www.coursera.org/learn/making-architecture
|
97%
|
785 |
Saving Money for the Future
|
5,454
|
4.6
| 30 |
Brian Walsh
|
SoFi
|
['retirement savings', 'setting financial goals', 'saving money', 'planning for retirement', 'paying for college']
|
This course is designed for anyone who currently has, or will have in the future have, savings goals. Learners will come to understand the importance of compounding growth, the variables that impact setting goals like retirement savings, and how much money you need to save now to reach future goals. The course will help learners think through individual goals, like retirement, but also how those goals fit into your bigger financial picture. For example, saving for retirement, buying a home, and funding college for your kids all at the same time. The instructors will also cover how preparing for emergencies can prevent the derailment of those financial goals. The concepts covered in this course are broad but through the activities offered, learners will see how to apply what they are learning about saving money for the future to their lives now. This course is geared towards learners in the United States of America. This module will help you understand how your savings will grow and how much you need to set aside for emergencies while you set your long-term financial goals. 9 videos8 readings7 assignments This module will identify the factors that go into setting a retirement target and the types of funds to help you reach that goal. 15 videos9 readings5 assignments This module will focus on other long-term financial priorities/major purchases, including buying a home or a car. It will help assess true costs for each and the different funds that can help you reach these goals. 4 videos6 readings4 assignments This module focuses on the ways you can prepare to pay for your child's education, including how much it will likely cost, different types of funding, and the different types of accounts you can use to reach this goal. 6 videos6 readings7 assignments1 plugin
|
4 modules
|
Beginner level
|
9 hours to complete (3 weeks at 3 hours a week)
|
https://www.coursera.org/learn/saving-money-future
| null |
786 |
Global Diplomacy – Diplomacy in the Modern World
|
191,819
|
4.7
| 4,968 |
Dr J. Simon Rofe, SOAS, University of London
|
University of London
|
['Policy Analysis', 'Art', 'History', 'International Relations']
|
The Global Diplomacy course is a unique offering to the MOOC environment. Bringing together cutting edge research in the broad fields of Diplomatic and International Studies, award winning distance learning delivery and the instructors previous experience of delivering a successful MOOC. Please see the volume Global Diplomacy: Theories, Types and Models authored with Dr Alison Holmes, (Westview, 2016), and the Understanding Research Methods MOOC from Coursera. The Global Diplomacy MOOC has a direct heritage in the University of London International Academy/SOAS Global Diplomacy MA Programme launched in April 2013 which have attracted hundreds of students from around the world. The Global Diplomacy MA Programme is provided by the Centre for International Studies and Diplomacy which has been teaching postgraduate courses in Diplomacy for over twenty five years.
After completing the 'Global Diplomacy' MOOC, learners will have:
1. The ability to demonstrate a critical understanding of the nature and development of global diplomacy, drawing on a variety of relevant contributing disciplines in the broad field of International Studies.
2. An understanding of changes in diplomatic practices and procedures and the relationship of those changes to contemporary politics.
3. A sound grounding in both theoretical and empirical approaches to debates in diplomacy so that students have been exposed to the and skills needed to analyse global diplomacy.
4. knowledge of issues in global diplomacy in historical and contemporary contexts. Welcome to Global Diplomacy: Diplomacy in the Modern World. 3 readings In this E-tivity we will question the nature of diplomacy and construct a definition. 2 videos2 readings1 peer review Welcome to the second week of Global Diplomacy: Diplomacy in the Modern World. This module will explore what constitutes Success and Failure in Diplomacy 2 videos2 readings1 peer review Welcome to the third week of Global Diplomacy: Diplomacy in the Modern World. This module will discuss qualities of a 'good' diplomat. 3 videos2 readings1 peer review Welcome to the fourth week of Global Diplomacy: Diplomacy in the Modern World. This module will explore where we see diplomacy in action. 1 video2 readings1 peer review Welcome to the final week of Global Diplomacy: Diplomacy in the Modern World. In this module we reflect on what we have learnt about diplomacy. This extra challenge exercise will add to your understanding. 12 videos3 readings1 peer review
|
6 modules
| null |
13 hours to complete (3 weeks at 4 hours a week)
|
https://www.coursera.org/learn/global-diplomacy
|
98%
|
787 |
Work with Gemini Models in BigQuery
|
Enrollment number not found
|
Rating not found
| null |
Google Cloud Training
|
Google Cloud
|
[]
|
This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks. This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks. 5 videos1 reading1 assignment2 app items
|
1 module
|
Intermediate level
|
3 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/work-with-gemini-models-in-bigquery
| null |
788 |
Introduction to Android Mobile Application Development
|
68,353
|
4.6
| 1,327 |
Taught by Meta Staff
|
Meta
|
['Android Studio', 'Application development', 'Mobile Development']
|
This course is an ideal stepping stone if you want to become a mobile developer. We’ll introduce you to this career path and give you a high-level overview of programming and the tools needed to develop Android applications. Explore the Android Studio and the fundamental concepts of Android app development. Learn about operating systems and different platforms for creating mobile apps. You’ll conclude your introduction to Android application development by building out each aspect of a guided project. In this module, you will learn the general principles of mobile apps and the Android platform ecosystem. 14 videos10 readings4 assignments2 discussion prompts In this module, you will set up and explore the Android Studio environment. 12 videos7 readings3 assignments In this module, you will explore how to create a video player app in Android Studio, from project planning to project launch. 11 videos9 readings4 assignments1 discussion prompt
|
3 modules
|
Beginner level
| null |
https://www.coursera.org/learn/introduction-to-android-mobile-application-development
|
98%
|
789 |
Maximizing Miles: Enhancing EV Range & Efficiency
|
Enrollment number not found
|
Rating not found
| null |
Prasanth Kumar Palani
|
Coursera Instructor Network
|
['Sustainability', 'Efficiency', 'EV', 'Electric', 'range']
|
Electric vehicles (EVs) have gained immense popularity in today's rapidly evolving automotive landscape due to their sustainability and environmental benefits. However, one of the critical aspects that influence an Electric vehicle's adoption is its range and efficiency. This Electric Vehicle Range and Efficiency course is designed to provide a comprehensive overview of the factors affecting an EV's range and efficiency, strategies for maximizing it, and technologies contributing to energy efficiency. We will discuss the impact of vehicle weight, aerodynamics, and tire selection on an EV's efficiency. We’ll also review cutting-edge solutions such as lightweight materials, low rolling resistance tires, and advanced battery management systems. We’ll also analyze the need for expanding the charging infrastructure and how it enables faster adoption of electric mobility at a global level
This program is designed for anyone who wants to learn about electric vehicle range and efficiency.
It is recommended for the learner to have some basic knowledge of electric vehicle components and their architecture. Learners who have completed the other basic courses on electric vehicles can also attend this course.
By the end of this course, learners will be well-equipped to make informed decisions about EV usage, optimize their driving habits, and apply these learnings if they are already working or about to work on an electric vehicle project. This course on Electric Vehicle Range and Efficiency is designed to provide a comprehensive overview of the factors affecting an EV's range and efficiency, strategies for maximizing it, and technologies contributing to energy efficiency. We will discuss the impact of vehicle weight, aerodynamics, and tire selection on an EV's efficiency. 11 videos4 readings1 assignment
|
1 module
|
Beginner level
|
2 hours to complete
|
https://www.coursera.org/learn/maximizing-miles-enhancing-ev-range--efficiency
| null |
790 |
Generative AI Content Creation
|
Enrollment number not found
|
Rating not found
| null |
Instructor not found
|
Organization not found
|
['Image Editing', 'Creativity', 'Generative AI', 'Graphic Design', 'Adobe Firefly']
| null | null | null |
1 hour to complete
|
https://www.coursera.org/learn/generative-ai-content-creation
| null |
791 |
State Estimation and Localization for Self-Driving Cars
|
51,558
|
4.7
| 823 |
Jonathan Kelly
|
University of Toronto
|
[]
|
Welcome to State Estimation and Localization for Self-Driving Cars, the second course in University of Toronto’s Self-Driving Cars Specialization. We recommend you take the first course in the Specialization prior to taking this course. This course will introduce you to the different sensors and how we can use them for state estimation and localization in a self-driving car. By the end of this course, you will be able to:
- Understand the key methods for parameter and state estimation used for autonomous driving, such as the method of least-squares
- Develop a model for typical vehicle localization sensors, including GPS and IMUs
- Apply extended and unscented Kalman Filters to a vehicle state estimation problem
- Understand LIDAR scan matching and the Iterative Closest Point algorithm
- Apply these tools to fuse multiple sensor streams into a single state estimate for a self-driving car
For the final project in this course, you will implement the Error-State Extended Kalman Filter (ES-EKF) to localize a vehicle using data from the CARLA simulator.
This is an advanced course, intended for learners with a background in mechanical engineering, computer and electrical engineering, or robotics. To succeed in this course, you should have programming experience in Python 3.0, familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses), Statistics (Gaussian probability distributions), Calculus and Physics (forces, moments, inertia, Newton's Laws). This module introduces you to the main concepts discussed in the course and presents the layout of the course. The module describes and motivates the problems of state estimation and localization for self-driving cars. An accurate estimate of the vehicle state and its position on the road is required at all times to drive safely. 9 videos3 readings1 discussion prompt The method of least squares, developed by Carl Friedrich Gauss in 1795, is a well known technique for estimating parameter values from data. This module provides a review of least squares, for the cases of unweighted and weighted observations. There is a deep connection between least squares and maximum likelihood estimators (when the observations are considered to be Gaussian random variables) and this connection is established and explained. Finally, the module develops a technique to transform the traditional 'batch' least squares estimator to a recursive form, suitable for online, real-time estimation applications. 4 videos3 readings3 assignments2 ungraded labs Any engineer working on autonomous vehicles must understand the Kalman filter, first described in a paper by Rudolf Kalman in 1960. The filter has been recognized as one of the top 10 algorithms of the 20th century, is implemented in software that runs on your smartphone and on modern jet aircraft, and was crucial to enabling the Apollo spacecraft to reach the moon. This module derives the Kalman filter equations from a least squares perspective, for linear systems. The module also examines why the Kalman filter is the best linear unbiased estimator (that is, it is optimal in the linear case). The Kalman filter, as originally published, is a linear algorithm; however, all systems in practice are nonlinear to some degree. Shortly after the Kalman filter was developed, it was extended to nonlinear systems, resulting in an algorithm now called the ‘extended’ Kalman filter, or EKF. The EKF is the ‘bread and butter’ of state estimators, and should be in every engineer’s toolbox. This module explains how the EKF operates (i.e., through linearization) and discusses its relationship to the original Kalman filter. The module also provides an overview of the unscented Kalman filter, or UKF, a more recently developed and very popular member of the Kalman filter family. 6 videos5 readings1 programming assignment1 ungraded lab To navigate reliably, autonomous vehicles require an estimate of their pose (position and orientation) in the world (and on the road) at all times. Much like for modern aircraft, this information can be derived from a combination of GPS measurements and inertial navigation system (INS) data. This module introduces sensor models for inertial measurement units and GPS (and, more broadly, GNSS) receivers; performance and noise characteristics are reviewed. The module describes ways in which the two sensor systems can be used in combination to provide accurate and robust vehicle pose estimates. 4 videos3 readings1 assignment LIDAR (light detection and ranging) sensing is an enabling technology for self-driving vehicles. LIDAR sensors can ‘see’ farther than cameras and are able to provide accurate range information. This module develops a basic LIDAR sensor model and explores how LIDAR data can be used to produce point clouds (collections of 3D points in a specific reference frame). Learners will examine ways in which two LIDAR point clouds can be registered, or aligned, in order to determine how the pose of the vehicle has changed with time (i.e., the transformation between two local reference frames). 4 videos3 readings1 quiz This module combines materials from Modules 1-4 together, with the goal of developing a full vehicle state estimator. Learners will build, using data from the CARLA simulator, an error-state extended Kalman filter-based estimator that incorporates GPS, IMU, and LIDAR measurements to determine the vehicle position and orientation on the road at a high update rate. There will be an opportunity to observe what happens to the quality of the state estimate when one or more of the sensors either 'drop out' or are disabled. 8 videos2 readings1 programming assignment1 discussion prompt
|
6 modules
|
Advanced level
| null |
https://www.coursera.org/learn/state-estimation-localization-self-driving-cars
|
95%
|
792 |
Developing Applications with Cloud Run Functions on Google Cloud
|
Enrollment number not found
|
Rating not found
| null |
Google Cloud Training
|
Google Cloud
|
[]
|
In this course, you learn about Cloud Run functions, Google's serverless, fully-managed functions as a service (FaaS) product that lets you implement single-purpose function code that reponds to HTTP requests and events from your cloud infrastructure. Introduction to the course content. 1 video An introduction to Cloud Run functions, what they are, and their benefits and use cases. 5 videos1 assignment1 app item Learn how to trigger and call Cloud Run functions, and how to connect them in workflows and to cloud resources in your network. 4 videos1 reading1 assignment1 app item Secure access to Cloud Run functions, learn about function identity and how to protect data used by functions. 3 videos1 assignment Learn how to integrate Cloud Run functions with Cloud databases. 3 videos1 reading1 assignment1 app item Learn how to use best practices with functions. 2 videos1 assignment Review of course content. 1 video
|
7 modules
|
Intermediate level
|
5 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/developing-applications-with-cloud-functions-on-google-cloud
| null |
793 |
SAS Advanced Programmer Professional Certificate
|
9,040
|
4.8
| 323 |
Peter Styliadis
|
SAS
|
[]
|
When you complete this professional certificate program, you will have experience in SAS programming using SAS 9 and will be able to process data using Structured Query Language in the SAS environment, use the SAS macro facility to design, write, and debug dynamic macro programs, and use advanced DATA step techniques and procedures to manipulate data. These skills prepare you for the SAS Advanced Programming Professional certification exam. Applied Learning Project Two projects are included as honors lessons in this professional certificate program. Each project will demonstrate your comprehensive knowledge of the learned SAS programming skills. In the first project, you use SQL to analyze to analyze passenger claims at United States airports. In the second project, you use the SAS macro language to automate reporting and analysis of analysis of supplier sales. Course Description In this course, you learn about Structured Query Language (SQL) and how it can be used in SAS programs to create reports and query your data.
“By the end of this course, a learner will be able to…”
● Query and subset data.
● Summarize and present data.
● Combine tables using joins and set operators.
● Create and modify tables and views.
● Create data-driven macro variables using a query.
● Access DBMS data with SAS/ACCESS technology. In this course, you learn advanced techniques within the DATA step and procedures to manipulate data. Course Learning Objectives: (3+ per course)
“By the end of this course, a learner will be able to…”
● Perform text substitution in SAS code.
● Use macro variables and macro functions.
● Automate and customize the production of SAS code.
● Conditionally or iteratively construct SAS code.
● Write self-modifying, data-driven programs. In this course, you learn advanced techniques within the DATA step and procedures to manipulate data. “By the end of this course, a learner will be able to…”
● Use additional functions (LAG, FINDC/FINDW, and COUNT/COUNTC/COUNTW).
● Perform pattern matching using PRX functions.
● Process repetitive code, rotate data, and perform table lookups using arrays.
● Perform table lookups and sort data using hash and hash iterator objects.
● Create numeric templates using the FORMAT procedure.
● Create custom functions using the FCMP procedure. Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review. When you complete this Professional Certificate, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹ When you complete this Professional Certificate, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹ Illinois Tech Degree ¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information. This Professional Certificate has ACE® recommendation. It is eligible for college credit at participating U.S. colleges and universities. Note: The decision to accept specific credit recommendations is up to each institution.Learn more
|
3 course series
|
Intermediate level
| null |
https://www.coursera.org/professional-certificates/sas-advanced-programmer
| null |
794 |
Paths to a Sustainable Future
|
Enrollment number not found
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Rating not found
| null |
European University For Transition
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ESSEC Business School
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[]
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This MOOC is an introduction to social and ecological transition. Ecological issues (climate change, loss in biodiversity, scarcity of resources, etc.) and their
social consequences (growing inequalities, poverty, conflicts, forced migrations, etc.) call
upon us to promote a paradigm shift, to redesign our production and consumption patterns,
as well as our lifestyles. This is what transition is all about.
In this MOOC, you will encounter some of the changes needed for transition at different
levels: worldviews (political), systems (the economy, management...) and lifestyles (at
personal and community levels). Following the MOOC will help change your way of thinking
or living, as well as to transform the structures of society. You will learn about possible
existing solutions, and also see that new solutions need to be invented. This MOOC will also
highlight the importance of working with others.
Anyone can follow the course, without prerequisites. If you already have some knowledge of
the topic, it will allow you to discover a number of approaches to transition and strengthen
your understanding of both challenges and ideas for change.
This MOOC was developed by the European University For Transition Erasmus + project.
The European University for Transition (EU4TRANSITION) Erasmus + project developed innovative learning and research practices (e.g. new curricula, teaching methods, institutional network) to accompany the transition in the education field. It developed multidisciplinary, pragmatic and holistic approaches for teaching and learning in the field of « Transitions » and facilitate the exchanges, flows and co-creation of knowledge and, more specifically, skills.
Partners were: ESSEC BUSINESS SCHOOL, UNIVERSITEIT VOOR HUMANISTIEK, UNIVERSIDAD PONTIFICIA COMILLAS, ARTERRA BIZIMODU, YASAR UNIVERSITESI, MTÜ EESTI ÖKOKOGUKONDADE ÜHENDUS and CAMPUS DE LA TRANSITION.
More information at: https://eu-4-transition.essec.edu/home
This project has received funding from Erasmus Plus under grant agreement N°2020-1-FR01-KA203-080465.
Disclaimer: the European Commission’s support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein. Welcome to this MOOC on transition! The MOOC was designed as follows: 1) A first module to address challenges at the level of worldviews: a worldview is apolitical vision of the future. 2) A second module to address the social implications of transitions in diverse fieldssuch as the economy, business, accounting, etc… 3) A third module to address the practical implications of transitions in our daily lives: wecalled this module “Tools for Transition”. Of course, all aspects of ecological and social transition will not be covered in this MOOC: we have selected some topics to illustrate the three levels mentioned above. This will not say everything about transition, but the MOOC will illustrate these three levels. Before starting, let us make a statement of principle: transition calls for philosophical andpolitical debates, leaving space for different sensitivities and priorities. This MOOC was built by a group of partners from diverse institutions: universities and eco-villages. In this MOOC, each contributor will speak in his own name. Even if all the contributors agree on the seriousness and urgency of the ecological situation, and the need to change unsustainable lifestyles, they may differ concerning the means to be taken to achieve it. This MOOC will help you raise your awareness of this diversity; it will help you understand the debates atstake and, ultimately, develop your ability to build your own personal critical thinking. We wish you all the best for this journey into the social and ecological transition! 1 video3 readings Welcome to the first module called “New Worldviews Related to Transition”. We will show how important worldviews are in shaping the way we build the future. 10 videos1 reading1 assignment Welcome to this module on the social implications of transition. By “social” we mean the structures of society, which can be described either as “fields” such as the economy,management, law and public policy, or as organizations such as private companies, public administrations or regulatory bodies. In this module, we will focus on the fields of management and the economy, as well as on private companies. 13 videos1 reading1 assignment After a module on the political level of worldviews, and a module on the structural level of the social implications of transition, we will now move to the level of daily life at the level of individuals and groups. We called this module “Tools for Transition”. 8 videos1 reading1 assignment
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4 modules
|
Beginner level
|
5 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/paths-to-a-sustainable-future
| null |
795 |
AWS Pricing
|
Enrollment number not found
|
Rating not found
| null |
LearnKartS
|
LearnKartS
|
['AWS Support Plans', 'Billing Management', 'AWS Pricing Models', 'AWS Pricing']
|
Welcome to the AWS Pricing course! This course is designed to equip you with the knowledge and skills necessary to understand and navigate the various pricing models and cost management tools offered by AWS. While introductory courses provide a basic overview, this advanced course delves into the complexities of AWS pricing structures, enabling you to optimize your cloud spending and achieve cost efficiency in your AWS environment.
The course is aligned with the AWS Cloud Practitioner Certification exam structure and will help you prepare for the certification exam.
This course requires a fundamental understanding of cloud computing and basic AWS services.
By the end of this course, you will be able to:
- Evaluate AWS pricing models and structures.
- Utilize the AWS cost calculator to estimate and manage billing effectively.
- Analyze AWS support plans and understand the AWS Marketplace.
This course combines engaging videos, demos, assignments, and readings to provide you with a comprehensive learning experience. This module provides an overview of AWS pricing models and support plans. By the end of this module, learners will understand AWS pricing structures, utilize the cost calculator, select appropriate support plans, and manage billing effectively. 3 videos1 reading2 assignments1 discussion prompt Explore the intricacies of AWS pricing models and support plans in this comprehensive module. Learn to navigate the AWS cost calculator, select optimal support plans, and master effective billing management strategies to optimize cost efficiency and support needs. Gain the skills needed to make informed decisions and maximize value within the AWS ecosystem. 3 videos2 readings3 assignments1 discussion prompt
|
2 modules
|
Intermediate level
|
3 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/aws-cloud-practitioner-certification-aws-pricing
| null |
796 |
Writing in First Person Point of View
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11,032
|
4.7
| 113 |
Ariel Levy
|
Wesleyan University
|
['English Language', 'Creative Writing', 'Storytelling', 'memoir']
|
If you have always wanted to tell your own story—in a memoir, first-person essay, or any other form of autobiographical non-fiction—but felt you lacked the tools or the framework, this is the class for you. We will learn how successful first-person writing is structured to offer the reader a sense of propulsive motion, and is guided by a narrator who is deliberately crafted. We will explore the ways in which language can be used to create tone, so that the emotional freight of your words is as potent as the storytelling. And crucially, we will consider the writer's responsibility to the reader: the importance of being a guide who includes the reader in the sensory, emotional, and intellectual experience you mean to share through your writing. 4 videos1 peer review 4 videos1 peer review 4 videos1 peer review 3 videos1 peer review
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4 modules
| null |
5 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/first-person-pov
| null |
797 |
Developing Applications with Cloud Run on Google Cloud: Fundamentals
|
Enrollment number not found
|
Rating not found
| null |
Google Cloud Training
|
Google Cloud
|
[]
|
This course introduces the Cloud Run serverless platform for running applications. In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle.
You learn about service identities, how to control access to services, and how to develop and test your
application locally before deploying it to Cloud Run. The course also teaches you how to integrate
with other services on Google Cloud so you can build full-featured applications. Introduction to the course structure, and contents. 1 reading Understand the fundamentals of Cloud Run that include its resource model, and the container
lifecycle. Learn how autoscaling works and how to control access to your Cloud Run services. 6 readings1 assignment Learn how service accounts provide Cloud Run service identities, and how you can control access
to Google APIs by implementing the principle of least privilege. Also, learn how to use secrets and
environment variables in your applications that run on Cloud Run. 1 video5 readings1 assignment1 app item Learn how to develop and test applications to run on Cloud Run. Manage service deployments and revisions on Cloud Run,
and learn how to integrate your Cloud Run service with other services in Google Cloud. 4 readings1 assignment1 app item Review the topics discussed in the course. 1 reading
|
5 modules
|
Beginner level
|
4 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/developing-applications-with-cloud-run-on-gcp-fundamentals
| null |
798 |
Entrepreneurship 2: Launching your Start-Up
|
59,641
|
4.8
| 1,963 |
Kartik Hosanagar
|
University of Pennsylvania
|
['Strategic Management', 'Brand', 'Choosing Advisors', 'Brand Management', 'Entrepreneurship']
|
Once you have a prototype and a clearer vision of the opportunity, you’ll need to create a small organization to discover how to create a repeatable and scalable business model. Designed to provide you with a comprehensive overview of the critical components of creating a start-up, Entrepreneurship 2: Launching the Start-up, provides practical, real-world knowledge about the lean approach, the minimum viable product, when to pivot, when to quit your day job, the art of the pitch, building and managing a team, allocating equity, and building your external team, advisory board members, professional services, and entrepreneurial strategy. At the end of this course, you’ll be able to create a strategy for launch, including knowing who you need to hire, how to manage them to provide the greatest value, and what legal aspects are involved. You’ll also be prepared for Entrepreneurship 3: Growth Strategies. This module was created to give you the information you need to begin to take your validated opportunity, build an MVP, and begin to design a winning pitch. Smart entrepreneurs can avoid wasting time by designing an initial product that only serves the core needs of its customers, and may be able to avoid an unnecessary pivot by finding the right product-market fit early on. By the end of this module, you'll understand if your product is truly minimally viable, know why an MVP is a good strategy, be able to design a strategy to validate your hypothesis, identify the key components of a successful pitch, and decide whether or not to quit your day job. 8 videos1 reading1 assignment This module was designed to give you critical insights into the often-overlooked dynamics of founding team formation, early hires, and allocation of equity. You'll examine the research that shows why the composition of the founding team can be an important indicator of future revenue, why some motivations of the team are more profitable than others, how to get the right hires for your team, common mistakes in hiring key players, and why equity allocation is so vital to a start-up's survival. By the end of this module, you'll be better prepared to position your start-up for success by making data-driven decisions about your founding partners, your early hires, your first managers, and equity allocation. 7 videos1 reading1 assignment In this module, you'll learn about your external team: the advisors, mentors, and professionals you'll need to give your start-up the best possible chance for success. Many start-ups either ignore or over-invest in professional advisors, accountants, and lawyers. You'll explore what kinds of professionals you should hire, when to do so, and for how long. You'll also cover the differences between patents, intellectual property, and trade secrets so that you know what kind of protection you need. And you'll examine the various legal entities your enterprise may assume, so you can choose the appropriate entity for your venture. By the end of this module, you'll be able to define the legal form of your enterprise, the best way to protect your idea, how to determine what professional services will be most useful, and how to apply theories of social networks to make the most suitable choices for your set of advisors. 5 videos1 reading1 assignment In this module, you'll examine a variety of proven strategies to set your venture up for success. You'll learn a proven process for choosing a name for your venture, and explore successful strategies for developing a brand personality. You'll also explore existing resources in the entrepreneurial ecosystem, and dive deeply into entrepreneurial strategies. By the end of this module, you'll be able to take your product or service to market with a name, a brand, a strategy that positions your venture for success. 7 videos2 readings1 assignment
|
4 modules
| null |
8 hours to complete (3 weeks at 2 hours a week)
|
https://www.coursera.org/learn/wharton-launching-startup
|
96%
|
799 |
Introduction to Microsoft Power Platform
|
3,269
|
4.7
| 39 |
Microsoft
|
Microsoft
|
['Data Platform', 'Microsoft Power Platform', 'Microsoft Dataverse']
|
Welcome to course 1 on Microsoft Power Platform Fundamentals! This course provides an overview of modules within the Power Platform ecosystem. You will gain a solid understanding of its capabilities & potential for building powerful business solutions, get insights into data connectors & their role in integrating, interacting with different data sources.
You will delve into Microsoft Dataverse, a secure scalable data platform at the core of Power Platform, understand how it allows you to define relationships between tables & entities, enabling efficient management & organization of your data, learn about its environments, which play a crucial role in separating & managing data & apps within Power Platform.
You will also discover how Power Apps empowers you to create applications tailored to your business needs, enhancing productivity & efficiency. Real-world examples, such as the Heathrow Airport customer case study, provide practical insights into successful Power Platform implementations.
Finally, you will also be introduced to the Exam PL-900.
By the end of the course, you will be able to:
1. Describe the components of Microsoft Power Platform, the business value for customers, & security of the technology.
2. Define the basic concepts of the Dataverse and ways you can connect and customize data connections to Microsoft Power Platform applications.
3. Recognize the value and capabilities of Power Apps & ways other organizations have leveraged this technology to build simple applications for their business. Learn about the components of Microsoft Power Platform, the business value for customers, and security of the technology. 12 videos15 readings4 assignments1 discussion prompt1 plugin
|
1 module
|
Beginner level
|
3 hours to complete (3 weeks at 1 hour a week)
|
https://www.coursera.org/learn/introduction-to-microsoft-power-platform
| null |
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