One Open Source Project per Day #74: ai-engineering-from-scratch - Build AI Full-stack Skills from Ground Up

The article describes "ai-engineering-from-scratch," a comprehensive, 20-phase curriculum with 435 lessons requiring about 320 hours of study. Unlike superficial tutorials, it teaches the underlying mathematics and builds core AI components like tokenizers and attention mechanisms from the ground up. The curriculum is unique because each lesson provides a reusable artifact, such as a prompt or agent, that can be immediately integrated into daily workflows.

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: - Online Reading : Browse all docs at aiengineeringfromscratch.com https://aiengineeringfromscratch.com . - 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 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 Welcome to my homepage to find more useful knowledge and interesting products.