Course Materials
| Week | Date | Topic | Slides | Data example | Extra materials | Due |
|---|---|---|---|---|---|---|
| 1 | 2026-03-24 | Multivariate data and covariance geometry | Lecture 1 | R demo: dependence measures | Probability review | — |
| 1 | 2026-03-26 | Principal Component Analysis: Foundations | Lecture 2 | — | — | — |
| 2 | 2026-03-31 | PCA in practice | Lecture 3 | R demo: PCA | Multivariate normal review | — |
| 2 | 2026-04-02 | Factor analysis | Lecture 4 | R demo: Factor analysis | — | — |
| 2 | 2026-04-05 | — | — | — | — | HW1 due at 11:59pm |
| 3 | 2026-04-07 | Clustering | Lecture 5 | R demo: clustering on penguins | — | — |
| 3 | 2026-04-09 | Mixture models and EM | Lecture 6 | R demo: GMM on penguins | — | — |
| 4 | 2026-04-16 | Canonical Correlation Analysis: foundations | Lecture 7 | — | — | — |
| 5 | 2026-04-21 | CCA, multivariate regression, and RRR | Lecture 8 | R demo: CCA and regression for stocks | — | — |
| 5 | 2026-04-23 | — | — | — | — | in-class Midterm |
| 5 | 2026-04-26 | — | — | — | — | HW2 due at 11:59pm |
| 6 | 2026-04-28 | Classification | Lecture 9 | Quick R demo: classification | — | — |
| 7 | 2026-05-05 | Regularization for high-dimensional linear regressions | Lecture 10 | R demo: Regularization with the Hitters Data | — | — |
| 7 | 2026-05-07 | parse PCA and Covariance Shrinkage | Lecture 11 | — | — | — |
| 8 | 2026-05-12 | Decision trees | Lecture 12 | — | — | — |
| 8 | 2026-05-14 | Bagging and Random Forest | Lecture 13 | R demo: trees, bagging and random forests | — | — |
| 8 | 2026-05-14 | — | — | — | — | HW3 due at 11:59pm |
| 6 | 2026-05-19 | Nonlinear unsupervised learning | Lecture 14 | — | — | — |
| 9 | 2026-05-22 | — | — | — | — | Project due at 11:59pm |