Free online version of Stanford's Fall 2011 Intro to AI course (opens in new tab)

Could anyone explain to me why the HN community seems to have a particular interest in AI compared to other more "academic" areas? I have seen quite some amount of AI resources here, but at the same time for most startups discussed here they aren't particularly related to AI. Just curious.

The course has the requirement: "A solid understanding of probability and linear algebra will be required."

Can anybody advise some books or online resources that one can use for 2 month to prepare himself for the course? Thanks.

This could be risky for Stanford. What happens when all the online students ace the class (demonstrating the curve was very easy), or get consistently better grades than the students enrolled at Stanford?

Looks like a good way to sell more copies of AIMA[1]. (Don't get me wrong, I'm a fan, with my own signed copy--but not necessarily enough of a fan to "upgrade" to the third edition.)

[1] http://aima.cs.berkeley.edu/

I took a version of this class (also taught by Norvig and Thrun) last year, and I definitely found it very enjoyable. I ended up taking it after CS 229 (which covers the mathematical underpinnings of machine learning with some rigor), so I unfortunately couldn't evaluate how good of an introductory course to AI it would be (having covered a lot of the concepts prior), but even still it was a class I enjoyed. Of particular interest was hearing the instructors draw parallels to their work (particularly with Google and the DARPA challenge), which made a lot of the theoretical concepts much more tangible and helped me recognize their practical applications.

you can also see a prior version of the class here: http://www.stanford.edu/class/cs221/

This reminds me of CS229, of which there's an online version: http://www.youtube.com/watch?v=UzxYlbK2c7E

It's considerable more focused in scope, presenting the mathematics behind some of the more popular algorithms extensively used in machine learning, which is a subset of artificial intelligence. The course starts off pretty slow, but quickly gains speed and momentum. By the end, you should be fairly comfortable with clustering and classification/regression, among other topics. The lecture notes are also fantastic.

I may be straying a little off topic but it's worth noting that many of the mentioned course material and much more from a wide variety of subjects can be found at http://www.academicearth.org/.

This place is filled with awesome. Maybe you know?

Could someone describe what sort of prerequisite knowledge is required for following along a course like this?

I wish they had a version of a class like this that was meant to fit more easily into spare time. I'll be taking 18 hours at my own university, and I don't think I'll be able to set aside enough time to put a serious effort into this class.

I find this approach interesting compared something like OpenCourseware. If I understand correctly, this is a very similar approach, with a graded portion not typically offered at something like Khan or Open Courseware?

I'm curious about any enrolment caps and what's next for this approach.

EDIT: missing word.

Very cool. I'll be taking the intro AI course at my school this semester, so it will be fun to compare. Definitely excited to hear what Thrun and Norvig have to say. I met a colleague of Thrun's in Tokyo earlier this summer. By far the most interesting conversation of the entire trip.

That is really cool. I've forwarded the link to a couple instructors in the CS dept at my school. It seems like a great chance for some of us in the frozen northern wastelands of Vancouver to see how we stack up against the best and brightest in the US.

I decided to sign up for the course (I don't think I can officially sign up until later this Summer) but I'm not sure that I'll have the time or that I can afford the text. I'm also a Sophomore CS student, so the work would be very challenging for me.

I'm considering trying to take this and get my university to give me credit for it (it's Stanford, from one of the guys that wrote the textbook and I am getting a grade). However, I'm thinking whatever this class costs may hold me back.

That's awesome. I wonder if I can convince my college to count it for credit.