Over the summer, Stanford announced that they would be offering their AI class online for free. It made headlines, and a few weeks later they announced that they would be offering their intro to databases class and their machine learning class as well.
I've been working through the material for all three classes so that I would know whether they were worth recommending to the high school students I work with, and also to satisfy my own personal curiosity about how the online classes would be conducted. Summary: The database and machine learning classes are excellent. Ironically, the AI class is pretty bad, even though it was the poster child for this wave of online offerings.
The database class is the most accessible. I believe it is a freshman class at Stanford, and I think most CS-oriented high schoolers would do just fine with it. As with many CS classes, it certainly helps to have a strong background in discrete math. Specifically, prior exposure to mathematical logic, set theory, and relations makes it significantly easier to follow the discussions of relational algebra and relational design theory. The videos are fast-paced and interesting. The randomized quizzes that you can take over and over until you get 100% are a brilliant way to empower students to keep working until they have achieved mastery. The online homework system for practicing queries against a live database works quite well, and the exercises cover a nice range of difficulty from easy to hard. The teacher's weekly "screenside chats" and vibrant forum community really make it feel like you're "taking a class" rather than just working through a sterile set of videos and exercises. The material is well organized and is generally posted two to three weeks ahead of time for those who want to get ahead. All in all, it's the best example I've ever seen of what online education can potentially be.
The machine learning class is of similarly high quality. It shares the same video technology and the same quiz engine. The machine learning class also features weekly programming assignments, using the free language Octave. The programming write-ups are very clear, and you can keep submitting your program until you get it perfect. The submission process is very easy. Unfortunately, I won't be able to recommend this class to many high school students. This class is a very math-centric approach to machine learning, and I think to fully appreciate the material you need to have a certain comfort level with the basics of linear algebra, and it helps to have seen multivariate calculus. I doubt many high school students have that mathematical background.
Interestingly, just a few months ago, I watched some videos on "iTunes University" of the Stanford machine learning class, taught by the same professor (Andrew Ng). It is instructive to contrast my experience watching those classroom videos with my experience in the online class. The classroom videos tended to be quite long and slow, watching the professor scrawl long mathematical derivations on multiple blackboards. Without being able to see and do the related homeworks and programming assignments, it became difficult to follow the material. In contrast, the online course videos are much more briskly paced (because they know you can pause or rewatch the video if you don't get something), and the assignments do a great job of solidifying the knowledge before moving on to the next topic. It's amazing how much better the overall experience is with the online class than just watching the videos of the classroom lectures.
As I said up top, the AI class is astonishingly bad compared to the other two. This is all the more surprising given that it is the one that gained the most widespread attention when it was announced. The website is much more poorly organized than the sites for the other two classes. The videos are poor quality - I mean this in both the literal sense (the video image is of a dimly lit piece of paper and the audio is muffled) and the content sense (the pace is much slower, failing to take advantage of the medium's ability to be paused or rewound). The questions interspersed in the video don't seem to be particularly well chosen to solidify knowledge; instead the questions are often just prompts to motivate the next topic -- you're not really expected to know the answer to the question when it is asked. This means that the only means to really solidify the knowledge is the homework quiz. These quizzes are poorly presented (rather than a clearly expressed, written statement, you have to listen to the instructor verbally explain the question) and there is no immediate feedback. Unlike the other two classes, the quiz is not randomized, so there is one set of questions and then you must wait a week to compare your answers against the correct answers (and the mechanism for checking your answers is somewhat clunky). The whole thing seems like the profs weren't ready to go prime time with this class. Three weeks into the class, the classroom forum section was still "coming soon", for example. In fact, when I last looked, they had completely punted on the forum section, and the page just said to "use Reddit" instead. Also, the videos tend to be posted quite late. Honestly, if I had nothing to compare it to, I might think it was okay, but relative to the other two classes, it is mediocre at best.
If I were to judge the AI class solely in terms of its content, rather than on its presentation, my review wouldn't be any better. The class is really a breadth survey of various topics in AI, with no programming to back it up. Unless you're going to dig in and actually program some of these things, I really don't see the point. I believe the actual Stanford version of the class offered a programming component, but that it was dropped from the online class for logistical reasons. This is understandable, but it really takes away from the value of the class. One reason the machine learning class is so much better is because they did find a way to incorporate programming assignments.