Intro to AI: Teaching Resources

This repository contains a set of unplugged and plugged learning activities designed to help undergraduate students intuitively understand core AI concepts before transitioning to formal mathematics and programming.

Repository Contents

├── Classification/
│   ├── Printable Cards/
│   ├── Student Workbook/
│   ├── Jupyter Notebook/
├── Hidden Markov Models/
│   ├── Two Spies Activity Guide/
│   ├── Two Spies Student Game Sheets/
│   ├── Markov Models Jupyter Notebook/
│   ├── Particle Filter Lab Jupyter Notebook/
├── Imitation Game/
│   ├── Activity Guide/
├── Markov Decision Processes/
│   ├── Red and Black Jack Activity Guide/
│   ├── Value Iteration Jupyter Notebook/
├── Probability/
│   ├── Sherlock Pgmpy Lab Jupyter Notebook/
├── Reinforcement Learning/
│   ├── Q-Maze Activity Guide/
├── Search/
│   ├── Becoming Search Activity Guide/
│   ├── Becoming Search Uninformed Printable/
│   ├── Becoming Search Informed Printable/
│   ├── Grid Knockout Activity Guide/
│   ├── Grid Knockout Jupyter Notebook/
└── README.md

Included Materials

• Activity guides for each unplugged exercise
• Printable cards, maps, grids, and role sheets
• Slides demonstrating a proposed lesson sequence
• Jupyter notebooks mirroring each in-class activity with Python implementations
• Discussion prompts and example reflection questions

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Contact

For questions or collaboration:

jreddig3@gatech.edu