AI Engineering from Scratch

free

AI-native self-learning course to build neural networks, transformers, and LLMs from first principles

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About AI Engineering from Scratch

AI Engineering from Scratch is a free, open-source curriculum with 260+ lessons across 20 phases that teaches you to build neural networks, transformers, and LLMs from first principles using raw mathematics. The course covers programming in Python, TypeScript, Rust, and Julia, with every lesson including runnable code and real projects including building a GPT, RAG system, and agent teams. The entire structured path progresses from calculus and linear algebra through production deployment without any paywalls or gatekeeping.

Key Features

260+ lessons across 20 phases
Build algorithms from raw mathematics without wrappers
Multiple programming languages (Python, TypeScript, Rust, Julia)
Runnable code for every lesson
Real projects including GPT, RAG systems, and agents
Structured progression from math through production deployment
Free and open source with no paywall
AI glossary for jargon clarification

Use Cases

Learning AI engineering fundamentalsBuilding neural networks from scratchUnderstanding transformers and LLMsImplementing production AI systemsMulti-agent system developmentGaining deep mathematical understanding of AI