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One Open Source Project per Day #74: ai-engineering-from-...
WonderLab · 2026-05-24 · via DEV Community
Cover image for One Open Source Project per Day #74: ai-engineering-from-scratch - Build AI Full-stack Skills from Ground Up

WonderLab

Introduction

ai-engineering-from-scratch is a hardcore and comprehensive curriculum for AI engineering. Instead of just teaching you how to call the OpenAI API, it takes you through the underlying mathematical principles, step-by-step, building Tokenizers, Backpropagation, Attention mechanisms, all the way to autonomous agent swarms.

The entire curriculum consists of 20 phases and 435 lessons, requiring approximately 320 hours of study. What makes it unique is that every lesson ships a reusable artifact: a prompt, a skill, an agent, or an MCP server that you can immediately plug into your daily workflow.

Core Features

  • Build from Scratch Philosophy: Follows the principle that the best way to understand something is to build it by hand. You implement algorithms with raw math/Python before moving on to frameworks like PyTorch.
  • Full Spectrum Coverage:
    • Math Foundations: Linear algebra to neural network first principles.
    • ML & DL Core: From classical ML to the evolution of Transformers.
    • Generative AI: Principles of image, video, and audio generation.
    • LLM Engineering: Training, fine-tuning, quantization, and production deployment.
    • Agent Engineering: ReAct loops, memory, multi-agent coordination, and autonomous systems.
  • Output-Oriented: At the end of each lesson, you don't just "learn" something; you gain a transferable tool (e.g., a .md skill file for Claude/Cursor).
  • Multi-language Support: Primarily Python, but includes TypeScript, Rust, and Julia implementations.

How to Get Started

There are three ways to dive into the curriculum:

  1. Online Reading: Browse all docs at aiengineeringfromscratch.com.
  2. Clone & Run:

    git clone https://github.com/rohitg00/ai-engineering-from-scratch.git
    cd ai-engineering-from-scratch
    python phases/01-math-foundations/01-linear-algebra-intuition/code/vectors.py
    
  3. Agent-Driven (Recommended): If you use Claude, Cursor, or any agent with the curriculum skills installed, run /find-your-level. A 10-question quiz will map your knowledge to a personalized starting phase.

Conclusion

If you're tired of "one-minute prompt hacks" and want to truly master the underlying logic of AI while building your own arsenal of engineering tools, ai-engineering-from-scratch is the most thorough and high-quality resource available today.


Project URL: rohitg00/ai-engineering-from-scratch


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