| 1 | 1/20 | Introduction (Ch1) | 1/22 | Supervised Learning (Ch2) |
| 2 | 1/27 | Linear Algebra Review HW0 due (1/28) | 1/29 | Probability Review |
| 3 | 2/3 | Bayesian Decision Theory and Parametric Methods (Ch3,4) | 2/5 | Multivariate Methods (Ch5) (HW1 posted) |
| 4 | 2/10 | Dimensionality Reduction (Ch6) | 2/12 | (Quiz 1) |
| 5 | 2/17 | Clustering (Ch7, (B*)Ch9) | 2/19 | HW1 due (2/20), (HW2 posted) |
| 6 | 2/24 | Non-parametric Methods (Ch8) | 2/26 | (Quiz 2) |
| 7 | 3/3 | Linear Discrimination (Ch10); Midterm Review | 3/5 | HW2 due (3/6) |
| 8 | 3/10 | Spring Break | 3/12 | Enjoy your break! |
| 9 | 3/17 | Neural Networks (Ch11) | 3/19 | Neural Networks |
| 10 | 3/24 | Midterm (3/24) | 3/26 | Modern Deep Learning, (HW3 posted) |
| 11 | 3/31 | Backprop Recap & Midterm Discussion | 4/2 | (Quiz 3) |
| 12 | 4/7 | Kernel Machines (Ch14) | 4/9 | HW3 due (4/10) |
| 13 | 4/14 | Decision Trees (Ch9) | 4/16 | (HW4 posted) |
| 14 | 4/21 | Random Forests (Ch9); Model Comparison and Case Studies | 4/23 | (Quiz 4) |
| 15 | 4/28 | Graphical Models (Ch15); Final Review | 4/30 | HW4 due (5/1) |
| 16 | 5/5 | Study Day | 5/7 | Study Day |
| Final | 5/13 | 8am-10am | — | — |