So far, the difference in quality between and is remarkable.

ml-class is exceedingly well done, with fun and interesting programming assignments, lectures that are easy to follow and build properly from easy to harder, critiques of assumptions and common issues with the techniques, quizzes during the lectures that are at the right difficulty and only on material just covered.

ai-class has no programming assignments, no discussion forums, lectures that skip material and jump over key sections (just compare the discussion of linear regression in the two classes), and quizzes that jump from absurdly easy questions to questions on material not covered to unpleasantly time-consuming and error-prone questions (like lengthy probability calculations that require painfully churning through calculations by hand). The production values are also much lower, with bad lighting, no prepared slides, quiz questions that are badly embedded in the video sometimes even covering material in the slide you need to see, and outages on the site.

I hate to criticize classes that are generously being offered for free and involve a lot of hard work from many. But, for those of us taking these classes in part to look at examples of new models of education, I do think it is useful to evaluate these examples and, for that purpose, I think ml-class is by far a better example of how to do this well. If you are taking only ai-class (or started ai-class and gave up), I'd definitely recommend taking a look at ml-class for comparison.
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