I took this class a couple of years ago. It's outdated and overrated imho, with nowhere enough mathematical rigor to be useful. For example, the discussion of support vector machines (and classification in general if I recall correctly) was limited to two dimensions so that you didn't need linear algebra. The class also spends a lot of time on problems like path finding that you should be able to solve with your standard CS algorithms toolkit or just "logic" rather than needing to reach for anything that deserves the name "artificial intelligence" (at least today). Prof. Winston furthermore spends way too much time on vague truisms that may sum up or organize what's in his brain but aren't helpful to students. ("What if the answer doesn't depend on the data at all? Then you've got the trying to build a cake without flour.")

I hate to dismiss something as ambitious as this course and just tell people to blindly follow trends, but my honest advice would be to just skim these notes if you're interested and go take a normal machine learning course instead.