Hands-on labs for the main ideas in Polson and Sokolov, Bayes, Artificial Intelligence, and Deep Learning, from probability rules to neural networks. Each lab opens with a worked example loaded and ends with exercises to run live in class. Course page: AII 600.
Open a lab next to the topic you are teaching. The preset buttons load the worked examples, so the board shows a case students can recognize.
Each lab ends with "Try this in class" steps. They work as short guided exercises: change one setting, predict, then check.
Published numbers are used as given. Where the raw data isn't available, the lab simulates it from the example's model and labels it as simulated.