A multi-session workshop teaching AI/ML from first principles — from hand-built perceptrons to agentic systems.
Two tracks: a 3-session technical route and a 1-2 session non-technical user route.
| Session | Topic | Material | Demos |
|---|---|---|---|
| 01 | Foundations | Perceptrons, backprop from scratch, PyTorch intro | session01-perceptron, session01-nn-scratch, session01-xor-pytorch |
| 02 | Modern Approaches | MNIST CNN, custom models, fine-tuning, RAG, research frontiers | session02-mnist, session02-custom |
| 03 | Agentic Systems | ReAct agents, tool use, agentic SaaS landscape | session03-agent |
Requires Python 3.12 and UV.
# Install dependencies
uv sync
# Run the interactive menu
uv run sand
# Or run a specific demo directly
uv run sand session01-perceptronuv run sand Interactive menu
uv run sand session01-perceptron Single-layer perceptron (AND, OR, XOR)
uv run sand session01-nn-scratch Neural network from scratch (XOR)
uv run sand session01-xor-pytorch PyTorch XOR solution
uv run sand session02-mnist CNN on MNIST digits
uv run sand session02-custom Feedforward on Iris dataset
uv run sand session03-agent Mock ReAct agent loop
- rich — terminal UI (tables, panels, progress bars)
- torch — PyTorch deep learning framework
- torchvision — datasets and transforms (MNIST)
- scikit-learn — datasets and preprocessing (Iris)