Milestones
Milestones
New to milestones? Skim the NHANES worked example — one complete illustrative project from M0 to the Final Portfolio.
The Assignment Schedule lists every milestone alongside the weekly assignments in date order.
Milestones move the term project from team setup to final portfolio. They are short checkpoints, not separate side projects. Each one should make the next stage easier to complete and easier for another person to review.
Submission Contract
For every milestone:
- commit and sync the required files before submitting
- submit the GitHub repository link on Canvas
- include the latest commit hash in the Canvas comment box
- use relative paths
- document any package or data access requirements
- disclose and audit AI use
Milestone Map
| Milestone | Timing | Focus | Link |
|---|---|---|---|
| M0 | Week 4 | Group formation and repository access | M0: Group Formation |
| M1 | Week 6 | Project proposal and data intake | M1: Project Proposal |
| M2 | Week 7 | Preliminary analysis and Table 1-style summary | M2: Preliminary Analysis |
| M3 | Week 10 | Draft report and dashboard-style update | M3: Project Update |
| M4 | Week 11 | Peer review and reproducibility feedback | M4: Peer Review |
| Presentation | With Final Portfolio (Dec 11) | Narrated slide deck (online) | Presentation |
| Final Portfolio | Final deadline | Complete project record | Final Portfolio |
Project Points and Score Ownership
Project scores use direct points that match the course weights: M1–M4 are 5 points each, the Presentation is 10 points, and the Final Portfolio is 35 points. Staff record a score directly from zero to the stated maximum using the existing checklist as the evidence guide; there is no separate performance-band conversion, contribution multiplier, or adjustment formula.
Shared project artifacts receive one group score. Only a component that a brief already identifies as individually authored receives an individual score. The current M1–M4, Presentation, and Final Portfolio deliverables are shared project artifacts, so each currently receives one group score.
Reproducibility Expectations
Milestone work should be reviewable in GitHub Codespaces or a documented local setup. Keep data access clear, use relative paths, and avoid manual edits to generated outputs unless the edit is explicitly documented.
AI-Use Expectations
AI tools may help with drafting, code review, debugging, and clarity checks. Students remain responsible for correctness. Each milestone includes an AI-use note so reviewers can see what was AI-assisted and what was verified by the team.
Definition Of Done
A milestone is ready when the required files are present, the repository is synced, the Canvas submission points to the correct commit, and another student could understand what changed without private explanation.