# Syllabus: AINS6009 Capstone Project

## Catalog Description

Guides students through a complete AI project from charter through final defense and handoff.

## Course Structure

Each week includes readings, a lecture/slide sequence, an executable lab, and an applied deliverable. Students maintain a reproducible project record and submit work through the LMS or GitHub workflow selected by the instructor.

## Weekly Schedule

| Week | Topic | Essential Question | Deliverable |
|------|-------|--------------------|-------------|
| 1 | Problem definition and project charter | What problem will the capstone solve, and for whom? | Lab notebook + assignment brief |
| 2 | Literature, market, and domain review | What prior work and constraints shape the solution? | Lab notebook + assignment brief |
| 3 | Architecture and data plan | What system design can satisfy the charter? | Lab notebook + assignment brief |
| 4 | Prototype implementation | What is the smallest useful working system? | Lab notebook + assignment brief |
| 5 | Evaluation and iteration | What evidence shows progress or exposes failure? | Lab notebook + assignment brief |
| 6 | Deployment and operational readiness | What must be true before real-world use? | Lab notebook + assignment brief |
| 7 | Thesis, documentation, and defense | How will the work be defended to technical and nontechnical audiences? | Lab notebook + assignment brief |
| 8 | Final demonstration and handoff | What does the completed project prove? | Lab notebook + assignment brief |

## Assessment

| Component | Weight |
|-----------|--------|
| Weekly labs and notebooks | 30% |
| Applied assignments | 35% |
| Participation and technical critique | 15% |
| Final synthesis portfolio | 20% |

## Graduate Expectations

Submissions must show technical reasoning, evidence awareness, clear limitations, and responsible use of AI assistance. Code and analysis should be reproducible enough for instructor review.