🗓️ Weekly Schedule
| Week | Topic | Readings | Assignments |
|---|---|---|---|
| 1 | Fundamentals of AI | Week 1 Readings | Reflection Essay |
| 2 | AI Systems & Data | Week 2 Readings | Data Analysis |
| 3 | Ethics & Bias | Week 3 Readings | Bias Case Study |
| 4 | Policy & Governance | Week 4 Readings | Policy Analysis |
| 5 | Employment & Economics | Week 5 Readings | Employment Analysis |
| 6 | AI in Society | Week 6 Readings | Domain Analysis |
| 7 | Midterm Review | Review Materials | Midterm Exam |
| 8 | Case Studies | Case Studies | Case Study Report |
| 9 | Emerging Issues | Privacy & Surveillance | Privacy Analysis |
| 10 | Autonomous Systems | Autonomous Systems | Risk Assessment |
| 11 | Futures & Regulation | AI Futures | Policy Proposal |
| 12 | Final Projects | Project Resources | Final Project |
📚 Course Structure at a Glance
Each week includes:
- Required readings with discussion prompts and prep questions
- Assignments ranging from reflections to research projects
- In-class sessions for discussion and deeper exploration
- Optional office hours for questions and feedback
Grading breakdown:
- Weekly assignments (6 × 5%): 30%
- Midterm exam: 20%
- Case study presentation: 10%
- Final project: 30%
- Participation & discussions: 10%
Note: Dates and topics may be adjusted as needed. Check D2L for current assignments and deadlines.