@QingQ77: A full-stack AI engineering learning path from zero to mastery, 503 lessons covering from math basics to autonomous agent clusters, fully translated into Chinese with a dedicated website.

X AI KOLs Timeline Tools

Summary

A full-stack AI engineering learning path from zero to mastery, containing 503 lessons covering from math basics to autonomous agent clusters, with full Chinese translation and a dedicated website.

A full-stack AI engineering learning path from zero to mastery, 503 lessons covering from math basics to autonomous agent clusters, fully translated into Chinese with a dedicated website. https://t.co/hKSWy0pX2q
Original Article
View Cached Full Text

Cached at: 06/15/26, 01:02 PM

Start from scratch, implement every AI algorithm by hand
503 lessons · 20 stages · Python / TypeScript / Rust / Julia · Companion Chinese website aieng-zh.cn

Similar Articles

@Russell3402: A friend wanted to learn AI engineering, but I couldn't come up with a good learning path for a while. Here I recommend an open-source AI engineering learning curriculum! It aims to take you from the ground up, covering the complete AI engineering stack: from math, machine learning, deep learning, Transformers, LLMs, Agents, MCP, multi-agent…

X AI KOLs Timeline

Recommends an open-source AI engineering learning course, containing 20 stages and 503 lessons, covering from math fundamentals to production deployment, including Python and other languages, aiming to build a complete AI engineering system from scratch.

@FakeMaidenMaker: Full-Stack AI Engineer Roadmap: From Zero to Math, LLMs, and Agents – Covers Everything. There’s tons of AI material online, but it's all fragmented—one article on fine-tuning, another agent demo, every search yields "Build a RAG in 5 minutes" fast food. A coherent system from math to LLM to agent is nearly impossible to find.

X AI KOLs Timeline

A free, open-source AI engineering curriculum that covers math, LLMs, and agents across 20 phases and 435 lessons in Python, TypeScript, Rust, and Julia, designed to fill gaps in fragmented AI tutorials.

@Xudong07452910: Free and Open-Source High-Quality Tutorial Recommendation: 'Building an Agent from Scratch' - A systematic tutorial on Agent principles and practice from zero to advanced, covering: 1. Basic concepts and mainstream paradigms (ReAct, Plan-and-Solve, Reflection, etc.) 2.…

X AI KOLs Timeline

Recommend the free and open-source tutorial 'Building an Agent from Scratch', which systematically explains AI Agent principles and practice, covering mainstream frameworks such as ReAct, AutoGen, LangGraph, and multiple hands-on projects. It has received 53,000+ stars.