This audience-participation course will cover a single topic, "Lipschitz selection". Suppose that to each point x in a metric space X we associate a convex set K(x) in R^D. A "selection" is a map F:X->R^D such that F(x) lies in K(x) for each X in X. The goal of the course is to find an efficient algorithm to produce a selection whose Lipschitz norm is almost as small as possible. So far, I have only partial results. I hope the audience will come up with helpful ideas. No special background will be assumed.