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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 Building ML pipelines Tech session: Python + SQL Project proposal (Tue) Initial pipeline setup; analytical formulation and baselines
5 Sep 22 / 24 / 25 Performance metrics and evaluation, part 1: choosing metrics Project work 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 Temporal validation deep dive with project examples 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)

Verify against the official calendar. These dates are shifted forward from the Fall 2025 offering and assume classes begin Tuesday, Aug 25, with fall break Oct 13–16 and Thanksgiving break Nov 25–27. Confirm against the CMU academic calendar before the semester starts, particularly the last day of classes and the finals-week report deadline.