Week 9
Working with Datasets
Good sources, ethics, imports, exports, and data movement across systems.
Learning goals
- Reputable dataset sources
- CSV, XLSX, JSON, SQL basics
- Using APIs and internet data carefully
- Data dictionaries and metadata
- Ethics and privacy basics
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
Data Pipeline 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. Which is a strong public dataset platform?
Explanation: Kaggle is a well-known dataset platform.
Q2. Metadata helps explain?
Explanation: Metadata describes the data.
Q3. Sensitive personal data should be used?
Explanation: It must be handled carefully and ethically.