We spend a lot of time talking about supervised learning when discussing ML with students, but I find reinforcement learning just as interesting and useful.
I developed a talk on reinforcement learning for high school participants in SAIL ON, the year-round diversity and high school outreach program of the Stanford AI Lab that I initiated and led, which follows the SAILORS intensive two-week AI summer camp.
We discuss how reinforcement learning works, how to make decisions given Bayesian bounds, touchstone RL problems and recent applications, and where RL tends to succeed and fail.