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.