Im Noticing a lot of these courses are coursera, and one of the most frustrating things about the plattform is the fact that most courses close and access to course materials/videos etc. is revoked after the course is over, this destroys the whole point of a mooc for me, and this choice seems arbitrary.

Why cant education materials just be open and remain open to everyone, journals and textbooks included? There are enough tax paying citizens all over the world pumping money into our education systems that there is no reason it should not be freely available 24/7 to all.

The fact that unlimited free education still doesnt exist in 2015 makes me sad everytime I think about it.

The Design Of Computer Programs on Udacity by Peter Norvig is pretty awesome. As someone who's only been seriously programming for a year or two , each problem set went like this :

Write the code here to do X :

I write a messy 4 liner after lots of thinking.

Professor Norvig comes along and does it in a simple functional one liner.

Mind blown.

He teaches good functional style program design one epiphany at a time.

I've completed a bunch of Coursera courses. Quality really varies. Even within the 9 course Data Science specialization [1] track some courses were rather poor while the rest were very good. I'm currently taking the #5 rated course [2]. It is excellent. But I'm only taking it because the Statisical Inference course in the Data Science specialization was so weak.

I would also recommend the Cryptography 1 course by Dan Boneh on Coursera [3]. Excellent if you are at all interested in the subject.

I always download the lecture videos, slides, quizzes, labs and exams because, as mentioned, many of the courses don't allow access once the class is completed.

You definitely have to have plenty of self discipline to complete MOOCs. And I don't have any delusions about a Coursera certificate being useful in landing a job; that's not what I'm after. I'm building the skills I want to apply to my own projects.

[1] https://www.coursera.org/specializations/jhudatascience [2] https://www.coursera.org/course/statistics [3] https://www.coursera.org/course/crypto

I am surprised that Khan Academy is not recognized in this report probably because the scope is limited to just those offer by an accredited university. I think calculus and chemistry have helped many first and second years of college students taking introductory courses including myself. I think KA is probably the most popular MOOC for all ages, in the most accessible way given it only requires a YouTube account, which millions have for over a decade. But that's just my opinion.

YouTube has a few really amazing courses available online.

For example, UCB has a channel with up-to-date content that otherwise not available on MOOC platform.

* https://www.youtube.com/watch?v=QMV45tHCYNI is a very good class on data structure

* https://www.youtube.com/watch?v=HyUK5RAJg1c and the rest has very good lectures on theory of computation

* https://www.youtube.com/watch?v=_G6_-ljgmXE also very good for algorithms. I find MIT's version to be too theory based for practitioners. Anyway, I still watch MIT's just to complement anything missing (no two speakers can teach the same topic equally)

Interesting but... I enrolled and completed a couple of the courses listed there. I'd be interested in seeing for each what percentage of enrolled students actually completed the whole course. Anecdotally the numbers are really really low (as in "around 5%").

I'll just throw in a plug here for Prof. Abu-Mostafa's Learning from Data course at Caltech, which is outstanding: http://work.caltech.edu/telecourse.html

Unlike Andrew Ng's Coursera Machine Learning class, it is a real, unadulterated Caltech class, and exactly as challenging as that implies. It delves much more deeply into the mathematics behind ML, and the homework assignments are quite time consuming.

I took it as part of an interactive session through EdX, and the professor himself was extremely active on the forums: responding to student questions, clarifying lecture points, and giving homework suggestions--seemingly at all hours of the day and night.

I did #27 "Introduction to Mathematical Thinking" during Feb-April this year. I enjoyed it a lot and found it challenging without being impossible to complete. Finished with a distinction and a feeling of great satisfaction.

I'm now doing Coursera's Interaction Design specialisation [1], which is proving to be very informative and a lot of fun.

If you're considering doing a MOOC then I'd definitely recommend it. Choose a free, short-ish course to start with, make the commitment, and dive in.

[1] https://www.coursera.org/specializations/interaction-design

I found it very interesting that the second most popular Mooc of all time is a philosophy course.

Although personally I like better the philosophy introduction offered by MIT:

https://courses.edx.org/courses/MITx/24.00_1x/3T2014/info

I am also looking forward to this one https://www.edx.org/course/philosophy-minds-machines-mitx-24...

> An introduction to philosophy of mind, exploring consciousness, reality, AI, and more. The most in-depth philosophy course available online.

> What you will learn

The basics of argumentation

Some central arguments for and against the view that a sufficiently powerful computer can think (AI)

The main theories of mental states and their relations to physical states

Some central arguments for and against the view that the world is not as we perceive it to be

What the "hard problem of consciousness" is

I'm a big fan of uDacity, which only appears once in that list.

For a novice, their 'Intro to Computer Science' course is fantastic, as is the follow-on 'Web Development' course, led by Steve Huffman.

I've been doing Coursera courses for the past few years in an on/off fashion. I'm pleasantly

surprised by the courses that are more popular in this list.

I think the pattern is that the foundational or introductory courses are popular as they have a

larger audience. But it doesn't comment on the quality of the course. An interesting data point

is the social media "Share" widget that appears on the right column [0].

[0] https://www.coursera.org/course/rprog

I wonder how many of these were actually completed...

Enrolment would be an empty number to me, completion would be the mark of quality.

It's insufficient to measure Popularity as the total number of registrants. People browse through course offerings, register, and may never return.

Rating by the total number of students that completed a course would be even more revealing. Add a student retention rate, too. Etc etc.

I'm not sure whether the number of people enrolled in a course is a very good measure for the impact of a course. I agree with some other commenters that the number of people that completed a course isn't necessarily a good measure either. Some measure that includes the percentage of videos watched, exercises attempted, links followed, etc. would probably better represent the actual impact of a course.

Some considerations: all courses have lots of people that enroll to subsequently discover the course is hard, boring or otherwise not what they expected. I expect this number varies strongly per course. On the other hand, not attempting/passing exercises doesn't mean someone hasn't invested time in watching all lectures.

It's heartening there are so many math focused courses. With the Calculus course at https://www.coursera.org/learn/calculus1/ - I'm going over differential calculus right now, but I'm getting somewhat stuck on the Chain Rule, and in particular working out how to use it to differentiate 2^x.

The courses I've found so far haven't been all that helpful, even Khan academy is confusing me somewhat. Does this course explain things better?

Here is the list without 50 pagedowns:

  1. Programming Mobile Applications for Android Handheld Systems – Part 1 / University of Maryland
  2. Introduction to Philosophy / University of Edinburgh
  3. Inspiring Leadership through Emotional Intelligence / Case Western Reserve
  4. Introduction to Computer Science / Harvard University
  5. Data Analysis and Statistical Inference / Duke University
  6. Gamification / University of Pennsylvania / Wharton
  7. Social Psychology / Wesleyan University
  8. Circuits and Electronics / MIT
  9. Think Again: How to Reason and Argue / Duke University
  10. Creativity, Innovation and Change / Penn State
  11. A Beginner’s Guide to Irrational Behavior / Duke University
  12. Learn to Program: The Fundamentals / University of Toronto
  13. Game Theory / Stanford University, University of British Columbia
  14. Greek and Roman Mythology / University of Pennsylvania
  15. Startup Engineering / Stanford University
  16. Computational Investing, Part I / Georgia Institute of Technology
  17. Financial Markets / Yale University
  18. Introduction to Artificial Intelligence / Stanford University
  19. Introduction to Computer Science and Programming / MIT
  20. Introduction to Financial Accounting / University of Pennsylvania / Wharton
  21. Modern & Contemporary American Poetry / University of Pennsylvania
  22. Machine Learning / Stanford University
  23. Data Analysis / Johns Hopkins Bloomberg School
  24. Introduction to Computer Science and Programming Using Python / MIT
  25. Science and Cooking: From Haute Cuisine to Soft Matter Science / Harvard University
  26. Introduction to Philosophy: God, Knowledge, and Consciousness / MIT
  27. Introduction to Operations Management / University of Pennsylvania / Wharton
  28. Introduction to Mathematical Thinking / Stanford University
  29. Justice / Harvard University
  30. A History of the World Since 1300 / Princeton University
  31. Creative Programming for Digital Media & Mobile Apps / University of London/ Goldsmiths
  32. Neural Networks for Machine Learning / University of Toronto
  33. Learn to Program – Crafting Quality Code / University of Toronto
  34. Critical Thinking in Global Challenges / The University of Edinburgh
  35. Statistics – Making Sense of Data / University of Toronto
  36. Introduction to Biology – The Secret of Life / MIT
  37. Drugs and the Brain / Caltech
  38. Introduction to Databases / Stanford University
  39. The Ancient Greek Hero / Harvard University
  40. Social Network Analysis / University of Michigan
  41. Health in Numbers: Quantitative Methods in Clinical & Public Health Research / Harvard University
  42. Introduction to Astronomy / Duke University
  43. Human Health and Global Environmental Change / Harvard University
  44. Software Defined Networking / Princeton University
  45. Introduction to Statistics: Descriptive Statistics / UC Berkeley
  46. Computing for Data Analysis / Johns Hopkins Bloomberg School of Public Health
  47. Functional Programming Principles in Scala / Ecole Polytechnique Federale de Lausanne
  48. The Camera Never Lies / University of London/ Royal Holloway
  49. Calculus One / Ohio State University
  50. Maps and the Geospatial Revolution / Penn State

I typically hate ranking lists like this, since I believe student completion rates are more important than enrollment. However, I did find some joy in finding a new MOOC I could add to the backlog of courses I need to take.

I'm a little surprised that there is no mention of iTunes University, or maybe that doesn't count as a MOOC. I know there are some very popular courses on there that are easy to access.

Surprise that a philosophy class ranked at number two. Other then that the list mostly looks like what you'd expect.

I'm surprised, no Jeff Ullman Automata?

It would be nice if the prerequisites for a course were listed more clearly.

I don't like education and universities and all that stuff, I would like them to release the videos and the text in the open, that I can learn my way, not in a supervised fashion, behind a login wall.

there's a MOOC aggregator to help keep on top of course offerings and it tracks programs globally: www.class-central.com