MOOCs: 31 Free Online Courses from World-class Universities
Massive Open Online Courses (MOOCs) have to be one of the most empowering innovations of the last decade. MOOCs have liberalized education by increasing access to knowledge and skills worldwide. People in Kenya and other parts of the world can now take world-class courses in prominent universities like Harvard, MIT and Stanford free of charge.
What are MOOCs?
While MOOCs are very similar to distance/online learning offered by many universities around the world, the main distinguishing factor is that MOOCs have little or no entry requirements, and are offered free of charge to participants. In many cases, the only thing you need to enroll in a MOOC is access to a computer and internet. Like distance learning, MOOCs will have a set timeline to complete assignments, and are delivered online through web platforms.
MOOC Platforms
edX
Edx is an online learning platform founded by Harvard and MIT. Currently, Edx hosts courses from more than 250 leading institutions and is used by more than 78 million people from around the world.
Coursera
Founded in 2012, partners with more than 275 leading universities and companies, and has more than 113 million users from around the globe.
Udacity
Founded at Stanford, Udacity offers 97 nanodegrees and courses to an estimated 16 million users.
Why take MOOCs?
Since most MOOCs are offered by professors at top universities, their best selling point is getting access to top quality education associated with those institutions. Foremost, MOOCs are a popular way to build practical skills and knowledge by taking courses from leading institutions of higher learning.
Since they are free, MOOCs are also an inexpensive way of testing whether a certain career path is right for you. For instance, if you are considering a career change to computer science, web development, or data science, you might want to enroll in a couple of MOOCs to get the feel of your prospective career.
How to select MOOCs?
Once you have decided to enroll for MOOCs, here are a few things to consider when selecting the best one.
Self-paced vs Instructor-paced Courses
In self-paced courses, you will have access to the course materials as soon the course begins. This means you will have more flexibility in how fast or slow you want to complete the course-work and assignments. On the other hand, in instructor-paced courses, the course material will be published periodically, limiting your flexibility in completing assignments. The course duration will also be way shorter for instructor-paced courses.
Prerequisites
While MOOCs in general have little entry requirements, some courses will recommend that you take them after completing other courses or skills. These recommendations are not strictly enforced but they are meant to ensure your success.
Certificates and Badges
In an ideal world you should earn a certificate after completing a course as proof of your achievement. However, most MOOCS charge between USD 39 to outrageous for certificates. The exception is a few big tech-sponsored courses that offer free badges. Whether or not to pay for MOOC certificates should be determined by your individual needs. Regardless, MOOCs remain a cheap and practical way to gain knowledge and skills from industry leaders.
It is important to note that if you want to earn a certificate, and you are ready to pay for it, you have to indicate at the beginning of the course that. In other words, you cannot add the certificate option after completing the course.
Harvard, MIT, Stanford Courses You Can Online for Free
If you decide to take MOOCs here is a list of 31 popular courses you might want to consider. These Business, Computer Science, Web Development, Data Science, and Artificial Intelligence courses are offered by Harvard, MIT and Stanford professors through edX, Coursera or Udacity. Though most courses in this list introductory, a few have prerequisites.
Free Business Courses
1. Designing Your Career
This short course will help you plan your career in a practical way. You’ll learn how to get into a new field you’re interested in, different ways to think about networking, how to approach job opportunities, and ways to build real professional relationships.
** Self-paced ** 5 weeks (2–5 hours per week)
2. Entrepreneurship: Becoming an Entrepreneur
This is one among four popular entrepreneurship MOOCs by Massachusetts Institute of Technology. From idea generation to market research, product design, and pitching, this course combines MIT’s expertise with real-world activities, debunking common entrepreneurship myths and helping you define your goals on your entrepreneurial journey, regardless of your prior experience. The other entrepreneurship course are:
- Entrepreneurship 101: Who is your customer?
- Entrepreneurship 102: What can you do for your customer?
- Entrepreneurship 103: Show Me The Money
3. Exercising Leadership: Foundational Principles
You will explore strategies for leading in a changing world filled with adaptive challenges. You will learn how to identify complex problems, understand the dynamics of authority, build trust, and navigate conflict, empowering you to tackle the leadership challenges that matter most to you.
**4 weeks (2–3 hours per week)
4. Managing Happiness
You’ll explore different definitions of happiness, understand its various influences, and develop personalized strategies for greater well-being, all while learning how to share these insights to spread happiness and love in the world.Explores the science of happiness and how to apply it in your personal and professional life.
** Self-paced **4 weeks (2–3 hours per week)
5. Entrepreneurship in Emerging Economies
This course focuses on empowering you to tackle problems in emerging markets by fostering creative solutions and entrepreneurial efforts. You’ll delve into various challenges across diverse sectors and geographic locations, learning to think with a bias toward action while addressing issues related to financing, scaling, branding, property rights, and progress assessment.
** Self-paced **06 weeks (3–5 hours per week)
6. Startup Success: How to Launch a Technology Company in 6 Steps
In this course, you’ll follow six practical steps that any entrepreneur can use to kickstart a successful business. You’ll explore topics like idea generation, team recruitment, financing, and growth strategies while learning to assess product ideas, build prototypes, attract your first customers, and navigate the complexities of leadership and investment.
** Self-paced ** 4 weeks (2–3 hours per week)
7. Shaping Work of the Future
** Self-paced ** 8 weeks (4–5 hours per week)
This course aims to address the evolving needs of workers, families, economies, and societies by examining the changing landscape of work and how firms can thrive while supporting quality jobs and careers. It emphasizes understanding the impact of new technologies on work and society and developing strategies to enhance job and career opportunities for the current and future workforce.
8. CS50’s Computer Science for Business Professionals CS50B
This course is aimed at equipping business people with the basics of computer science to empower to make technological decisions.
** Self-paced ** 6 weeks
9. Game Theory
Game theory explores the process of strategic decision-making in various situations with the aim of increasing chances of success in real-life situations. In this course, you’ll learn how to analyze games, predict outcomes, and make choices that maximize your success. By studying concepts like cooperation, competition, and rational decision-making, you’ll gain valuable insights into real-life scenarios and develop problem-solving skills that can be applied in economics, business, and everyday life.
** Self-paced ** 17 hours
Free Data Science Courses
10. Introduction to Computational Thinking and Data Science
This course is the first in a sequence of 2 courses designed to help people use programming to solve useful problems. The Second course is Introduction to Computer Science and Programming Using Python
**Instructor-paced **9 weeks(14–16 hours per week)
11. Introduction to Data Science with Python
This course will give you practical experience in using Python for data science challenges, from modeling to storytelling. You will master essential libraries and run machine learning models, preparing you for further Python studies in machine learning and AI.
** Self-paced ** 8 weeks (3 – 4 hours)
12. Databases: Relational Databases and SQL
This course, the first in a sequence of five databases courses is designed to help you understand relational databases, and master SQL. The other courses in the set are:
** Self-paced ** 2 weeks (8–10 hours per week)
13. R Programming Fundamentals
This beginner course will take you from installing R to basic statistical functions.
** Self-paced ** 6 weeks (2–3 hours per week)
14. Statistical Learning
This course will teach you the main tools used in statistical modeling and data science.
** Self-paced ** 11 weeks (3–5 hours per week)
15. Data Analysis: Statistical Modeling and Computation in Applications
This MIT course on edX delves into data analysis, statistical modeling, and computation applied to real-world scenarios. Explore practical applications of these essential skills to gain a deeper understanding of data-driven decision-making.
**Instructor-paced **16 weeks(10–15 hours per week)
16. Understanding the World Through Data
Unlock the power of data with this MIT course on edX. Gain valuable insights into understanding the world through data and discover how data science can inform decision-making and drive innovation.
**Instructor-paced **9 weeks(3–6 hours per week)
Free Web Development Courses
17. Introduction to Python Programming
Learn to solve practical problems with Python. You’ll learn the fundamentals of the Python programming language, along with programming best practices.
18. Web Programming with Python and JavaScript CS50W
This course will equip you with the expertise to create interactive web applications, from the backend with Python to the frontend with JavaScript, providing a comprehensive understanding of web development technologies.
** Self-paced ** 12 weeks (6–9 hours per week)
Free Computer Science Courses
19. Understanding Technology CS50T
This course is designed to help you understand your everyday hardware, the Internet, multimedia, security, programming, or web development better
** Self-paced ** 6 weeks
20. Computer Science 101
CS101 is a self-paced introductory course designed for individuals with no prior computer science experience. The course covers essential topics like the nature of computers, hardware, software, and the internet, making it accessible to anyone who can use a web browser.
** Self-paced ** 6 weeks (4–6 hours per week)
21. Introduction to Computer Science CS50x
CS50x is the first in the series of Harvard CS50 courses, and is easily the most popular tech MOOC out there. This introductory course offers a comprehensive and engaging exploration of computer science fundamentals, providing you with essential knowledge and skills in programming, problem-solving, and algorithmic thinking.
** Self-paced ** 12 weeks (6–18 hours per week)
22. Introduction to Programming with Scratch CS50S
This course is an introduction to programming using Scratch, a visual language that lets you create code by dragging and dropping blocks. You’ll learn programming basics like functions, return values, conditions, loops, and variables, which are valuable skills for other programming languages like Java and Python. This course is a great starting point for future programming courses.
** Self-paced ** 10 weeks (3–9 hours per week)
23. Introduction to Programming with Python (CS50P)
CS50P will introduce you to programming using Python, a popular language for general-purpose programming, data science, web programming, and more. This course is designed to teach you Python from the ground up. You’ll dive into essential topics like functions, variables, loops, and handling errors, gaining hands-on experience and practical skills to write and test code effectively.
** Self-paced ** 10 weeks (3–9 hours per week)
24. Introduction to Computer Science and Programming Using Python
This is the second course in a two-course sequence designed to help people solve problems through programming.
**Instructor-paced **9 weeks(14–16 hours per week)
25. Introduction to Game Development CS50G
Learn about the development of 2D and 3D interactive games in this hands-on course, as you explore the design of games such as Super Mario Bros., Pokémon, Angry Birds, and more.
** Self-paced ** 7 weeks (10–30 hours per week)
26. Mobile App Development with React Native CS50M
This intermediate course will help you build your own mobile app using React Native
** Self-paced ** 13 weeks (6 – 9 hours)
Free Artificial Intelligence/ Machine Learning Courses
27. Introduction to Artificial Intelligence with Python CS50AI
This course takes you through the fundamental concepts and algorithms behind AI, offering hands-on experience in areas like graph search, classification, optimization, and reinforcement learning. You’ll gain proficiency in machine learning libraries and the principles of AI, equipping you to create your own intelligent systems by the end of the course.
** Self-paced ** 7 weeks (10–30 hours per week)
28. Intro to Artificial Intelligence
You’ll learn the basics of modern AI including machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
** Self-paced ** 6 weeks (4–6 hours per week)
29. Introduction to Machine Learning Course
This course will teach you how to analyze real-world data from a machine learning perspective.
30. Machine Learning with Python: From Linear Models to Deep Learning
Explore the fascinating world of machine learning with this MIT course on edX. From linear models to deep learning, you’ll dive deep into the theory and practice of this transformative field, developing practical skills in using Python for machine learning applications.
**self-paced **4 weeks(2–3 hours per week)
31. Artificial Intelligence for Robotics Programming a Robotic Car
Learn how to program all the major systems of a robotic car from the leader of Google and Stanford’s autonomous driving teams.
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