rohitg00

ai-engineering-from-scratch

AI🌱 NEW PROJECT BOOST#Machine Learning #Deep Learning #Python#LLMs#Agents

// summary

AI Engineering from Scratch is a comprehensive 320-hour curriculum that guides students from fundamental linear algebra to building autonomous agent swarms. The course emphasizes an AI-native learning approach where students use AI coding agents to test their knowledge and build reusable tools throughout 20 distinct phases. By working across Python, TypeScript, Rust, and Julia, learners develop a professional portfolio of prompts, skills, and agents that can be deployed in real-world environments.

// technical analysis

AI Engineering from Scratch is a comprehensive, AI-native educational platform designed to bridge the gap between theoretical AI knowledge and professional engineering proficiency. By emphasizing a 'build from scratch' philosophy, the project forces learners to implement core algorithms in Python, TypeScript, Rust, and Julia before utilizing established frameworks, ensuring deep technical intuition. The curriculum is uniquely structured as an interactive, agent-assisted journey where every lesson results in a tangible, reusable artifact like a prompt, skill, agent, or MCP server, effectively turning the learning process into a production-ready toolkit.

// key highlights

Provides a multi-language learning environment covering Python, TypeScript, Rust, and Julia to broaden engineering versatility.

Features an AI-native design where students use coding agents like Claude Code to test their progress and receive personalized learning paths.

Ensures every lesson produces a reusable artifact, such as custom prompts, agents, or MCP servers, for immediate professional application.

Includes a built-in '/find-your-level' skill that uses a 10-question quiz to map existing knowledge to a specific starting phase.

Offers a massive, structured curriculum of 283+ lessons across 20 phases, ranging from fundamental linear algebra to complex autonomous agent swarms.

Prioritizes deep understanding by requiring students to build neural networks and algorithms from first principles before introducing frameworks like PyTorch or JAX.

// use cases

Building a portfolio of reusable AI tools, prompts, and agents

Learning AI concepts through hands-on implementation before using frameworks

Integrating AI-native learning with coding agents like Claude Code for skill testing

// getting started

To begin, visit the official website at aiengineeringfromscratch.com to browse the full lesson catalog and roadmap. You can start by setting up your development environment as outlined in Phase 0, or use the '/find-your-level' skill if you are using an AI coding agent to assess your current expertise and generate a personalized learning path.