Implement model internals, retrieval pipelines, and agent runtimes. Test them, inspect failures, and keep the code and evaluation results.

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Free, open source, MIT. Learn on the website, with a coding agent, or by running local code.

542 lessons. 20 phases. Python, TypeScript, Rust, Julia.

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Learning paths

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Gradient descent

Twenty starting points follow gradient descent on a quadratic loss. The graph shows their positions and mean loss after each update.

Adjust the learning rate in the lesson · Compare GD, momentum, and Adam in code

Projects

Three projects with staged starters, reference implementations, and local graders. Run commands from the repository root after setup. Starters fail until you implement the stages.