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This is a good introduction to statistics at the college level.  While the course is intended for people entering the life sciences it can be taken by anyone interested in statistics.  Lab exercises use the R programming language.  The lectures are very good.  Recommended.

I just started taking this mooc and already am very impressed. The lecturer is very good and the explanations are on point and clear. Obviously a lot of thought has gone into the presentation. The short animated breaks are great too. Highly recommended.

A rare glimpse into the Alice in Wonderland world of high finance.  Professor Mehrling makes this very complicated world accessible and understandable through his very engaging lectures.  This is the only economics course I have ever taken that was not deathly boring.  In fact it was very interesting and I looked forward to new videos each week.  Highly recommended. The professor uses balance sheets of banks and other market participants to explain how money market operations work.  You'll learn about things like the federal funds market, eurodollars, repos and reverses, acceptances, swaps, and bonds.  The over-riding idea of the course is that there is a hierarchy of money with central bank liabilities at the top and many different kinds of credit below that.  The professor also discusses money market dealers, where their profit comes from, and the difference between the inside and outside spread.  Much attention is also given to how all these mechanisms change during times of stress, for example when liquidity dries up like in the last crisis, and how central banks have had to take innovative steps to handle the crisis, mostly by vastly expanding their balance sheets.

This is an excellent course that guides you in a hands-on fashion through constructing many types of analytics models. Very useful. Highly recommended. This course goes very well with Intro Statistical Learning from Stanford Online. The Stanford class will give you a good conceptual overview of why you'd use different models and validation schemes, and this course will give you practical guided experience in doing just that.

This course will take you from basic definitions to being very comfortable manipulating and modeling with random variables. The lectures are excellent, very logical and clear. Highly recommended. You need Calculus 1 to take this course.

This is my review for the entire Johns Hopkins Data Science specialization on Coursera. These comments apply specifically to this course and generally to all the courses. At this point I've only seen six of them but I imagine the three yet-to-be released courses will be similar. First this was a great idea. A grand introduction to data science basics and methods from some real experts. However the execution was sorely lacking. Bottom line the courses are superficial and not worth the time compared to other data science mooc offerings. The courses are at best very light introductions. Are you going to learn statistical inference in a 4 week course? No. Machine Learning? No. R programming? No. Most people realize that but maybe not everyone does. I feel sorry for the students who take these courses and afterwards believe they have any real knowledge of these subjects. Besides the thin content, the instruction itself is bad. The instructors often seem to just ramble as if they haven't prepared at all. And when an instructor says 'You can learn about this on Wikipedia', I can't help but feel like 'What am I listening to you for then?' Dr Peng's lectures were better than the other two but this was still my overall impression. I've taken and passed many other Coursera and edX moocs. Usually the content and instruction is excellent. I'm sorry to have to write a negative review but tbh these courses were simply a waste of time, especially when you consider the many excellent alternatives, like Data Analysis and Statistical Inference from Duke, Machine Learning and Statistical Learning from Stanford, and The Analytics Edge and Introduction to Probability from MIT. Update July 2014: It's my understanding that these courses have been revamped. I have not taken any of the new offerings. So the criticisms I made above may not apply anymore.

Both courses were excellent. These courses are language agnostic. So taking these, even if you've seen the material before, is a great way to teach yourself a new programming language.

Excellent lectures. Good assignments. The assignments were crafted so that if you understood the algorithm your solution would run in a reasonable amount of time, otherwise the solution would take forever. So that in itself was a good check on your work. If you're teaching yourself programming and want to leave amateur status, you absolutely must learn algorithms, and this course will teach you all the most important methods. Highly recommended.

This course is destined to become THE online statistics course. Very good lectures, well explained, excellent speaker, professional level graphics, an accompanying free online textbook, and supporting websites of interactive tutorials and 'explore statistics' applets. Not only is this an excellent introductory statistics course, its production values set a new standard for other moocs to achieve. Very highly recommended.

I had no experience with databases but wanted to learn about the subject as part of teaching myself programming. The course was harder than I thought but well worth it. This is a tour de force overview of everything databases. After taking this course I am very confident I can intelligently choose and use database technology. Very good lectures.

Utterly fasincating. A great story very well told. History is not my thing but I really looked forward to hearing the new lectures every week. Whatever your politics or religion this bird's eye view of our history as we know it will be challenging and entertaining.

This course does a great job of explaining keys, scales, and chords, in terms of the basic building blocks of tones, semi-tones, and scale patterns; without dumbing things down; and without going into the physics of sound. It's really just what I'd hoped it would be. The mooc also has very good production values with explanatory visuals synchronized to the verbal explanations. The quizzes are challenging but doable. Highly recommended.