# GenAI classroom starters

FutureStackDev — Generative AI & Agentic AI.

```bash
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
```

Open the `.ipynb` for the lesson you are on. Each notebook is scaffolding with `TODO`s, not a finished solution.

| Lesson | Notebook |
|---|---|
| 1.1 Tiny language model | `lab_1_1_tiny_language_model.ipynb` |
| 1.2 Tokens and attention | `lab_1_2_tokens_and_attention.ipynb` |
| 1.3 Pick a model | `lab_1_3_pick_a_model.ipynb` |
| 2.1 Let the model use tools | `lab_2_1_tool_loop.ipynb` |
| 2.2 Search your documents | `lab_2_2_rag_chunking.ipynb` |
| 2.3 Better search + a score | `lab_2_3_hybrid_eval.ipynb` |
| 3.1 Prompt, search, or train? | `lab_3_1_decision_briefs.ipynb` |
| 3.2 Light fine-tuning | `lab_3_2_lora.ipynb` |
| 3.3 Serve the tuned model | `lab_3_3_serve_adapter.ipynb` |
| 4.1 Documents and pictures | `lab_4_1_docs_and_images.ipynb` |
| 4.2 Several agents | `lab_4_2_agent_graph.ipynb` |
| 5.1 Timeouts and fallbacks | `lab_5_1_reliability.ipynb` |
| 5.2 Put it in a container | `lab_5_2_docker_metrics.ipynb` |
| 5.3 Safety, privacy, spend | `lab_5_3_guardrails.ipynb` |
| 5.4 Industry capstone | `lab_5_4_capstone.ipynb` |