| Session # | Topic | Lecture | Exercises | Solutions | Documents | |
|---|---|---|---|---|---|---|
| 1 | Introduction to course and machine learning | HTML / PDF | See slides | N/A | Anaconda guide | |
| 2 | Introduction to Python | HTML / PDF | Notebook / HTML | Notebook / HTML | Reading | |
| 3 | Model and hyperparameter selection | HTML / PDF | Notebook / HTML | Notebook / HTML | Reading | |
| 4 | Supervised ML | HTML / PDF | Notebook / HTML | Notebook / HTML | Reading | |
| 5 | Unsupervised ML | HTML / PDF | Notebook / HTML | Notebook / HTML | Reading | |
| 6 | Explainability | HTML / PDF | Notebook / HTML | Notebook / HTML | Reading | |
| 7 | Fairness | HTML / PDF | Notebook / HTML | Notebook / HTML | Reading | |
| 8 | Causality – Heterogeneous treatment effects | HTML / PDF | Notebook / HTML | Notebook / HTML | Reading | |
| 9 | Causality – Double machine learning | HTML / PDF | Notebook / HTML | Notebook / HTML | Reading |
Download website
The full course website can be downloaded here. To access the website, you should first extract the files and then launch the file index.html, which opens a local copy of the website.