# Syllabus: AINS6201 Automation & Process Optimization

## Catalog Description

Examines automation, RPA, extraction, optimization, agentic workflows, controls, and business cases.

## 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 | Process discovery and workflow mapping | Which processes are good candidates for automation? | Lab notebook + assignment brief |
| 2 | Robotic process automation basics | How do rule-based and AI-assisted automation differ? | Lab notebook + assignment brief |
| 3 | Document and data extraction | How does AI convert unstructured work into structured workflows? | Lab notebook + assignment brief |
| 4 | Optimization and scheduling | How can models improve resource allocation? | Lab notebook + assignment brief |
| 5 | Agentic workflow orchestration | When should AI coordinate tools and humans? | Lab notebook + assignment brief |
| 6 | Controls, auditability, and failure handling | How do automated processes remain accountable? | Lab notebook + assignment brief |
| 7 | Change management and workforce impact | How should organizations adopt automation responsibly? | Lab notebook + assignment brief |
| 8 | Automation business case | What evidence justifies automation investment? | 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.