| 1 | Introduction | |
| 2 | Binary Classification | |
| 3 | Concentration Inequalities | |
| 4 | Fast Rates and VC Theory | |
| 5 | The VC Inequality | |
| 6 | Covering Numbers | |
| 7 | Chaining | |
| 8 | Convexification | |
| 9 | Boosting | Problem Set 1 due |
| 10 | Support Vector Machines | |
| 11 | Gradient Descent | |
| 12 | Projected Gradient Descent | |
| 13 | Mirror Descent | Problem Set 2 due |
| 14 | Stochastic Gradient Descent | |
| 15 | Prediction with Expert Advice | |
| 16 | Follow the Perturbed Leader | |
| 17 | Online Learning with Structured Experts | |
| 18 | Stochastic Bandits | |
| 19 | Prediction of Individual Sequences | Problem Set 3 due |
| 20 | Adversarial Bandits | |
| 21 | Linear Bandits | |
| 22 | Blackwell's Approachability | |
| 23 | Potential Based Approachability | |
| 24 | Final Project Presentation | |
