Table:
| Date | Week | Unit | Title | Guest | Lab |
|---|---|---|---|---|---|
| 1/23/25 | 1 | Intro | Introduction | None | NO LAB |
| 1/30/25 | 2 | Fairness | Algo Fairness I | Drew Calcagno (Google) | COMPAS |
| 2/6/25 | 3 | Fairness | Algo Fairness II | Fairlearn I | |
| 2/13/25 | 4 | Fairness | Fairness III | Ben Laufer (Cornell) | Fairlearn II |
| 2/20/25 | 5 | Fairness | Lifecycle | Intersectionality | |
| 2/27/25 | 6 | Transparency | Explainability I | Mateo Espinosa (Cambridge) | Data Cleaning |
| 3/6/25 | 7 | Transparency | Explainability II | NO LAB | |
| 3/13/25 | 8 | Transparency | Ads | SHAP | |
| 3/20/25 | 9 | Midterm Exam | LIME | ||
| 3/27/25 | 10 | Spring Break | |||
| 4/3/25 | 11 | Transparency | Explainability III | Valerie Chen | SHARP |
| 4/10/25 | 12 | Data Protection | Diff Privacy | Varun Babbar | DataSynthesizer |
| 4/17/25 | 13 | Data Protection | Diff Privacy | Tyler Simko | DataSynthesizer |
| 4/24/25 | 14 | Data Protection | Applied Ethics | Mackenzie Jorgensen | Final Review |
| 5/1/25 | 15 | Final Exam | Project OH |
Material Table:
| Week | Unit | Reading | Lecture Slides |
|---|---|---|---|
| 1 | Intro | intro slides | |
| 2 | Fairness | Introduction and Algorithmic Fairness | Lecture slides |
| 3 | Fairness | Introduction and Algorithmic Fairness | Lecture slides |
| 4 | Fairness | Introduction and Algorithmic Fairness | Lecture slides |
| 5 | Fairness | Responsibility in the Data Science Lifecycle | Lecture Slides |
| 6 | Transparency | Lecture Slides | |
| 7 | Transparency | Trustworthy Machine Learning talk | Lecture Slides |
| 8 | Transparency | Lecture Slides | |
| 9 | Midterm Exam | ||
| 10 | Spring Break | ||
| 11 | Transparency | Lecture Slides | |
| 12 | Data Protection | Lecture Slides | |
| 13 | Data Protection | Lecture Slides | |
| 14 | Data Protection | ||
| 15 | Final Exam |