6.034

[Junno]

This is a course on Artificial Intelligence. It is usually given both semesters - Fall and Spring - but each version puts a different emphasis on the material and approach. The Fall (recommended) version is given by Professor Patrick H. Winston, a key figure in the development of AI, who puts a little extra into every lecture. The approach is more theoretical and Winston shares some of the fascinating stories behind the evolution of AI as a field. Winston discusses the different topics in AI through the notion of representation and shares some of his "Gold Start Ideas" like: "Ask why 5 times", "Fresh look makes you smarter", "Don't use former or latter" and many others. The rest of the staff - TAs and recitation instructors - are excellent, especially Mike Klein, a very intelligent and approachable TA.
The Spring version of this course is more about application and less theory. I did the Fall version so I can't add much more here. Sorry.
The course is VERY intensive - there are 5 problems sets (aka "Labs") in which you're given huge amounts of Python code to figure out and add some functionality to. There are also 4 quizzes and 1 final which has 5 parts, 4 of which correspond to the 4 quizzes and they take the highest grade of the two. Meaning that if you did really bad on either the quiz or its corresponding part in the final, they will take the higher grade. Very nice of them
If you take this course you're probably going to have to deal with it on a daily basis as either lecture, tutorial, recitation or lab...so brace yourself. As mentioned the course uses the Python programming language so you'll need to know some of it basic functionality.
My personal opinion is that the course really gets you thinking about all sorts of things and especially about modeling and representing your ideas...which can later be turned into programs and ran on the computer. I thought there was too much emphasis put on the quizzes and test and not enough on the labs. There isn't much coding in this class and that's a shame because in a field like AI you learn by doing, testing and then doing again.