Summer School on Edge AI – Hands-On Lab

This repository accompanies the keynote "From Edge to Tiny: Reimagining AI in the Era of Generative and Embedded Intelligence".
It provides hands-on exercises on TinyML training and a distributed AI Inference simulator.

What’s Inside

• notebooks/01_tinyml_training.ipynb → Train & quantize a TinyML CNN (MNIST)
• notebooks/02_simulator_colab.ipynb → Colab-friendly step-by-step simulator
• app/streamlit_app.py → Interactive simulator UI (Streamlit)
• lib/simulate.py → Simulation logic (devices, workloads, policies)
• scripts/run_simulator.py → CLI runner for quick experiments
• INSTALL.md → Full installation instructions

Quick Start (Simulator Only)

git clone https://github.com/robertmora/distributed-edge-ai-lab.git
cd distributed-edge-ai-lab
python3 -m venv .venv
source .venv/bin/activate   # (Windows: .\.venv\Scripts\Activate.ps1)
pip install -r requirements.txt
streamlit run app/streamlit_app.py

Open http://localhost:8501 to explore.

Run in Colab

• TinyML Training

• Simulator

Requirements

• Python 3.7–3.12
• Streamlit, NumPy, Pandas, Matplotlib, NetworkX
• (Optional) TensorFlow for TinyML training notebook

See INSTALL.md and the slides for detailed instructions.

---

Have fun experimenting with TinyML and Distributed AI inference!