Week 11
Real Project II — Finance and Medical Data
High-caution domains, limitations, and practical model workflows.
Learning goals
- Finance data as noisy time series
- Why stock prediction is hard
- Medical classification basics
- Confusion matrix in risk screening
- Responsible communication of results
Suggested classroom flow
| Session | Focus | Output |
|---|---|---|
| Day 1 | Concept introduction and guided examples | Notebook or script |
| Day 2 | Hands-on lab and teacher walkthrough | Working code |
| Day 3 | Practice tasks and discussion | Assignment draft |
| Day 4 | Assessment and mini project | Submission |
Mini project
Risk and Trend Lab
Outcome for the week: students should finish with usable code, a short explanation, and at least one visual or result artifact.
Quick MCQ preview
Q1. Why is stock prediction hard?
Explanation: Financial markets are noisy and complex.
Q2. In screening, recall is important when?
Explanation: Recall matters when false negatives are costly.
Q3. Medical model results should be presented?
Explanation: Medical outputs need caution and context.