Weekly Materials
Each week has a problem focus, the official syllabus topic, the software tools involved, and an AI-aware validation task.
| Week | Focus | Main Tool |
|---|---|---|
| 1 | Arrays, scripts, and plots as computational objects | MATLAB |
| 2 | Functions, control flow, and debugging | MATLAB |
| 3 | Curve fitting, interpolation, and residual checks | MATLAB |
| 4 | Numerical methods and 3D visualization | MATLAB |
| 5 | Symbolic and numerical computation | MATLAB |
| 6 | R Markdown and visualization | R |
| 7 | Data transformation as question-answering | R |
| 8 | Exploratory data analysis | R |
| 9 | Import, tibbles, and tidy data | R |
| 10 | Joins, strings, factors, and dates | R |
| 11 | Pipes and reusable functions | R |
| 12 | Vectors, iteration, and repeated analysis | R |
| 13 | Model basics and diagnostics | R |
| 14 | Many models and grouped workflows | R |
| 15 | Communication, visualization, and synthesis | R |
Model Week
Weeks 1, 2, 3, and 4 are fully expanded model weeks. They include:
- a two-meeting teaching plan;
- a detailed MATLAB lab;
- an AI code critique activity;
- a student exercise set;
- multiple starter scripts.
The other weeks will follow this pattern as the course site develops.
Weekly Pattern
Each week follows the same rhythm:
- Start from a mathematical or statistical question.
- Build a small computational workflow.
- Use MATLAB or R to produce output.
- Check the output against expectations.
- Critique any AI-generated code or explanation.
- Save work in a reproducible form.