Schedule — Fall 2026
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Lectures are Tuesday and Thursday, 11:00am–12:20pm. Tech sessions and team check-ins are in the Friday lab section, 9:30–10:50am. See the syllabus for topic detail and readings, and the project page for deliverable descriptions.
Assignments listed in the "Due" column are due at the start of the listed day unless Canvas says otherwise.
✏️ The table below is generated from a Google Sheet. Edit the sheet, not this file — direct edits here are overwritten the next time the sync runs. See scripts/build_schedule.py for details.
| Week | Dates | Tuesday | Thursday | Friday (lab) | Due | Project focus |
|---|---|---|---|---|---|---|
| 1 | Aug 25 / 27 / 28 | Class overview | Scoping real-world ML Projects | Tech session: basic setup — ssh to the server, GitHub access, database access via psql and DBeaver | Tech setup form (Tue) Project preferences + data confidentiality form (Thu) |
Get familiar with the class, goals, and project options |
| 2 | Sep 1 / 3 / 4 | ML and Policy Case studies | Acquiring, Storing, Linking Data | Tech session: remote workflows | Data audit and exploration | |
| 3 | Sep 8 / 10 / 11 | Data exploration + 30 min team coordination | Project work | Tech session: git and GitHub | Data stories; finalize project scope | |
| 4 | Sep 15 / 17 / 18 | Analytical formulation and baselines | Baselines (continued from last session) | Tech session: Python + SQL | Project proposal (Tue) | Initial pipeline setup; analytical formulation and baselines |
| 5 | Sep 22 / 24 / 25 | Building ML pipelines | Performance metrics and evaluation, part 1: choosing metrics | Tech session: triage configuration | Peer reviews of three proposals (Tue) | |
| 6 | Sep 29 / Oct 1 / 2 | Performance metrics and evaluation, part 2: model selection and validation | Project Work | Check-ins begin | Project Update 1: Formulation & Baselines | Iteration 1 — end-to-end pipeline shell |
| 7 | Oct 6 / 8 / 9 | Feature engineering and imputation | Project work | Check-ins | Project Update 2: Triage Cohort and Labels | Iteration 2 — feature development |
| — | Oct 13 / 15 / 16 | Fall break — no classes | ||||
| 8 | Oct 20 / 22 / 23 | Features in triage | Triage office hours and Q&A | Check-ins | Project Update 3: Modeling Plan, Validation Setup, Feature List |
|
| 9 | Oct 27 / 29 / 30 | ML modeling in practice | Project work | Check-ins | Project Update 4: v0 Baseline Results and Features | Iteration 3 — models and evaluation |
| 10 | Nov 3 / 5 / 6 | No class — Election Day | Performance metrics and evaluation, part 3: model selection | Check-ins | Project Update 5: Initial ML Results and Planned Model Grid | |
| 11 | Nov 10 / 12 / 13 | Model interpretability | Ethics workshop | Check-ins | Project Update 6: ML Results Over Time | Iteration 4 — interpreting the models |
| 12 | Nov 17 / 19 / 20 | Bias and fairness | Project work | Check-ins | Project Update 7: Understanding Your Models | |
| 13 | Nov 24 | Field trials: validating ML models | Thanksgiving — no class | Thanksgiving — no class | Project Update 8: Model Bias and Fairness | Final model choice; performance and impact on disparities |
| 14 | Dec 1 / 3 / 4 | Wrap-up, final check-in, and presentation prep | Final presentations | Presentation overflow / project work | Final presentation | Presentations |
| Finals | Dec 9 | Final report, code, repo, documentation (Wed) |