[hlx]

A free, online version of "Introduction to Artificial Intelligence", taught by Sebastian Thrun and Peter Norvig.

(Peter Norvig is the Director of Research at Google, and Thrun does work for Google while directing research at Standord.)

"The class runs from Sept 26 through Dec 16, 2011. While this class is being offered online, it is also taught at Stanford University, where it continues to be a popular intro-level class on AI. For the online version, the instructors aim to offer identical materials, assignments, and exams, and to use the same grading criteria. Both instructors will be available for online discussions.
A high speed internet connection is recommended as most of the course content will be video based. Access to a copy of Artificial Intelligence: A Modern Approach is also suggested."

Online enrollment ends Sept 10th, sign up early!


Sourced from: http://www.ai-class.com/

You can sign up at that website. While you will be graded at the same standards of Stanford Students, online participants will only receive a certificate from the instructors.

I am taking this on. I was wondering if anyone else is interested? I would much like to form a "Study Group" of sorts.

[modi123_1]

I saw that earlier and book marked the link. I miss my old college zeal.

[xclite]

Huzzah. I'm in. I saw the article earlier. I've already taken a similar course, but I'd like to stay sharp. I also already have the book, which is basically a bible on AI. It's awesome.

[hlx]

I just finished loading the ebook version on my Kindle. Going to give it a good few reads over in preparation.

Hmmm... The bible of AI being taught by the Jedis of AI... interesting.

This post has been edited by hlx: 04 August 2011 - 02:13 PM

[modi123_1]

Haha.. I have the red covered first edition - that's how old school I am.

[RandomlyKnighted]

I want to but I will already be taking a full load this semester and just don't see myself having enough time for it.

[bennitto]

I've signed up for this

Its pretty much certain I will also be doing an AI course next school semester so hopefully this will help me stay ahead

[Brewer]

I'm going to check out a copy of the text for the class from my library and see whether I think I'll be able to fit it in to my schedule.

[look416]

i have just enrolled in, considering i might have a semester break during that time XD

[stackoverflow]

I signed up, not sure what I will gain from it other than some extra knowledge and a letter from the professors. I don't think it's much for a resume or anything, but will be good fun!

[xclite]

They also opened up Introduction to Databases and Introduction to Machine Learning.

[bennitto]

I would also love to sign up for intro to machine learning but due to a busy schedule and the possible challenge faced in intro to ai, i'll stick to 1 for now.

[Nikitin]

Regarding the Machine Learning class, be prepared to spend a considerable amount of time if you want to truly grasp it. You must be absolutely solid on Probability Theory , Linear Algebra, and Multivariate Calculus before beginning it. The way its taught at Stanford is very theoretical - more proofs than programming. I can hardly consider it a CS course.

There are already resources available for this class. I would advise checking out the notes for midway of the class (around 6th week / 12th lecture) and see whether the pace and math is bearable for you.

Otherwise, you'll likely find yourself completely lost 3/4 into the class, without a long-term grasp of the subject.

[bennitto]

@Nikitin: do you know what level of math is needed for Introduction to AI. I have taken a first year math course and I may need to brush up on it but it would be helpful to know.

[Nikitin]

Probability Theory and Linear Algebra as well. Depending on how much ML will be covered you might need to know a bit of Multivariate Calculus. Really, all these classes are usually taken after students complete their math prerequisites.

If you're comfortable with joint distributions, conditional probabilities as well as matrix algebra, you should be fine. Gradients and partial derivatives are needed for the ML portion. But since Into to AI is much more practical, you'll find yourself actually writing programs and not proving stuff.