# Syllabus: AINS6302 AI for Risk Assessment

## Catalog Description

Models cyber risk using assets, likelihood, impact, vulnerability prioritization, controls, reporting, and audit evidence.

## 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 | Cyber risk concepts and assets | What is at risk, and how is it valued? | Lab notebook + assignment brief |
| 2 | Threat likelihood and impact modeling | How can AI support risk estimation? | Lab notebook + assignment brief |
| 3 | Vulnerability prioritization | Which weaknesses matter most now? | Lab notebook + assignment brief |
| 4 | Scenario analysis and stress testing | How do we reason about uncertain attacks? | Lab notebook + assignment brief |
| 5 | Controls and residual risk | How do mitigations change risk? | Lab notebook + assignment brief |
| 6 | Executive reporting and risk communication | How should cyber risk be communicated to leaders? | Lab notebook + assignment brief |
| 7 | Governance, compliance, and audit | How do AI risk tools support formal obligations? | Lab notebook + assignment brief |
| 8 | Cyber risk assessment portfolio | What evidence supports risk decisions? | 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.