| Week 1 | Introduction to Python Programming | Link |
| | Homework and LaTeX | Link |
| Week 2 | Linear Algebra in Python | Link |
| Week 3 | Maximum Likelihood Estimation | Link |
| | Python: Sampling and Linear Regression | Link |
| Week 4 | Bayes Optimal Classifier | Link |
| Week 5 | Classification Methods: Logistic Regression, LDA, QDA, SVM | Link |
| | Midterm Review | |
| Week 6 | Support Vector Machine | |
| Week 7 | Introduction to Numerical Optimization | Link |
| Week 8 | Additive Models, Smoothing Splines, Ensemble Models | Link |
| | A Short Tutorial in pyGAM | Link |
| Week 9 | Ridge and LASSO Regression | Notes |
| Week 10 | Deep Learning in Practice (no in-person discussion sections) | Dive into Deep Learning |