AI BriefingAI Engineering from Scratch
Key point
An open-source AI engineering curriculum with 435 lessons covering everything from mathematical foundations to agents has been released.
Details
The AI Engineering from Scratch curriculum, which moves away from fragmented AI learning methods to organically connect theory and practice, has been released on GitHub.
This project consists of 20 stages and 435 lessons, and covers a wide range from linear algebra to autonomous swarms using 4 languages: Python, TypeScript, Rust, and Julia.
Rather than simple code copying or demo implementations, it repeats the process of reading a problem, deriving the mathematical principles, and then writing and testing code directly. In particular, by implementing core algorithms such as Backprop, Tokenizer, Attention, and Agent loop from scratch without libraries, it aims to provide a deep understanding of how frameworks like PyTorch work internally.
This curriculum is provided as open source, freely available to anyone via GitHub without any sign-up or cost.
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