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AI Engineering from Scratch

This ambitious open-source project offers a complete, 435-lesson curriculum to build AI engineering knowledge from the mathematical ground up. It appeals to HN's love for deep technical dives and self-directed, fundamental learning. Forget frameworks; here, you derive the math, write the code, and understand AI's inner workings.

22
Score
1
Comments
#11
Highest Rank
2h
on Front Page
First Seen
May 23, 5:00 PM
Last Seen
May 23, 6:00 PM
Rank Over Time
1911

The Lowdown

The "AI Engineering from Scratch" project presents a comprehensive, free, and open-source curriculum designed to teach AI engineering from its foundational mathematical principles. Developed by Rohit Ghumare and contributors, this resource aims to provide a deep understanding of AI concepts by having learners build every algorithm from first principles before introducing higher-level frameworks.

  • Scope: The curriculum comprises 435 lessons across 20 distinct phases, ranging from linear algebra to autonomous swarms.
  • Methodology: It emphasizes building algorithms directly from raw mathematics, ensuring that users understand the underlying mechanics before encountering tools like PyTorch.
  • Learning Process: Each lesson follows a structured loop: problem comprehension, mathematical derivation, code implementation, testing, and artifact retention.
  • Languages: The content leverages Python, TypeScript, Rust, and Julia, selected based on their suitability for specific concepts.
  • Accessibility: It's entirely open-source, designed to run on a personal machine, with no paywalls or sign-ups required.
  • Content Breadth: Phases cover a vast array of topics, including ML Fundamentals, Deep Learning Core, Computer Vision, NLP, Transformers, Generative AI, Reinforcement Learning, LLMs from Scratch, Agent Engineering, Multi-Agent & Swarms, Infrastructure, Ethics, Safety & Alignment, and Capstone Projects.
  • Current Status: All 435 lessons and 20 phases are completed and available.

This project stands out by offering a rigorous, hands-on path to mastering AI engineering, moving beyond surface-level understanding to truly grasp the mechanisms powering modern artificial intelligence.