Learning path

AI & Machine Learning Path

From your first model to something you can deploy. This path is being written up now - here is the outline we are working from.

Planned

Python & Data Tooling

NumPy, pandas and notebooks for exploratory work.

Planned

Classical ML

Regression, trees, evaluation and avoiding leakage.

Planned

Deep Learning

Tensors, training loops and PyTorch fundamentals.

Planned

LLMs & Embeddings

Prompting, fine-tuning and measuring output quality.

Planned

Retrieval & RAG

Vector search and grounding answers in your own data.

Planned

Deployment

Serving models, batching and cost control.

Other learning paths

Want to help write one of these? The handbook is open source.