Lecture 2: Uncertainty is now available on the course website. While we've so far focused on information our AI can know for sure (a game's optimal move, a mine's location, etc.), we'll now transition to how AI can model uncertain events. We'll start by looking at the mathematics of probability theory. Then, we'll explore models — including Bayesian networks and Markov chains — that AI can use to deal with uncertainty.

For your project this week, you'll have two choices (you only need to choose one): you can either use a Markov chain approach to implementing Google's PageRank algorithm for computing the importance of web pages, or you can use a Bayesian network approach to see how AI can be used to trace the inheritance of genetic traits through generations.

A few other importance announcements for this week:

All the best,
Brian