rohitg00/ai-engineering-from-scratch Alternatives

AI engineering education / curriculum

A free, MIT-licensed, from-scratch curriculum with 511 lessons across 20 phases teaching AI engineering (LLMs, agents, RAG, MCP, etc.) in Python, TypeScript, Rust, and Julia.

54.5kPythonMITactive · last push 1mo agoGitHub

Drop-in peers

Same problem, same approach. Swapping one for another is a config change, not a rewrite.

GokuMohandas/Made-With-MLGitHub

choose for a production-focused ML curriculum with more MLOps depth but less agent/LLM breadth.

Learn how to develop, deploy and iterate on production-grade ML applications.

: 49.2k
: Jupyter Notebook
: MIT

active7mo ago

Older generation, or narrower

An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.

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adongwanai/AgentGuideGitHub

choose for a focused Chinese-language guide on agents/RAG and interview prep, not a 511-lesson curriculum.

: 9.6k
: MDX
: none

active1mo ago

FareedKhan-dev/all-agentic-architecturesGitHub

choose for hands-on runnable implementations of 35 agent architectures instead of broad lessons.

35 production-grade agentic AI architectures (Reflexion, LATS, GraphRAG, MemGPT, Voyager, BrowserAgent, ...) — a Python library and runnable textbook with multi-provider LLM support and a 17-task benchmark leaderboard.

: 4.5k
: Jupyter Notebook
: MIT

active4mo ago

Snailclimb/AIGuideGitHub

choose for a practical Chinese guide to AI app development and job interviews.

AI 应用开发、AI 编程实战与面试指南，涵盖 LLM、Agent、RAG、MCP、Claude Code、Codex 等核心技术与工程实践。

: 611
: none

active3mo ago

microsoft/AI-For-BeginnersGitHub

choose for a quick, gentle 24-lesson intro to AI, not the full depth.

12 Weeks, 24 Lessons, AI for All!

: 68.5k
: Jupyter Notebook
: MIT

active1mo ago

dair-ai/Prompt-Engineering-GuideGitHub

choose for deep coverage of prompting/RAG/agents as a reference, not a complete curriculum.

🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

: 77.7k
: MDX
: MIT

active7mo ago

patchy631/ai-engineering-hubGitHub

choose for hands-on tutorials on LLMs/RAG/agents rather than a structured course.

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

: 37.5k
: Jupyter Notebook
: MIT

active1mo ago

mrdbourke/pytorch-deep-learningGitHub

choose to specialize in PyTorch deep learning rather than broad AI engineering.

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

: 18.8k
: Jupyter Notebook
: MIT

slowing8mo ago

bryanyzhu/agentic-ai-system-courseGitHub

choose for a concentrated course on production AI agents.

Use agent to learn agent - A skeleton course on how to design, build, and operate production AI agents

: 611
: JavaScript
: MIT

active4mo ago

stas00/ml-engineeringGitHub

choose for deep technical reference on training infrastructure and performance.

Machine Learning Engineering Open Book

: 18.7k
: Python
: CC-BY-SA-4.0

active2mo ago

MathFoundationRL/Book-Mathematical-Foundation-of-Reinforcement-LearningGitHub

choose for a mathematical deep-dive into RL theory, not the full curriculum.

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

: 17.8k
: MATLAB
: none

active1mo ago

decodingai-magazine/personalized-recommender-courseGitHub

choose for a project-based course on building recommender systems.

👕 Open-source course on architecting, building and deploying a real-time personalized recommender for H&M fashion articles.

: 651
: Jupyter Notebook
: MIT

active6mo ago

microsoft/ai-agents-for-beginnersGitHub

choose for a focused beginner course on building AI agents.

18 Lessons to Get Started Building AI Agents

: 74.7k
: Jupyter Notebook
: MIT

active1mo ago

jmaczan/tiny-vllmGitHub

choose to build an LLM inference engine from scratch in C++/CUDA.

Build your own high performance LLM inference engine in C++ and CUDA - a smaller version of vLLM

: 1.1k
: C++
: Apache-2.0

active2mo ago

Listed as an alternative to

These projects were analysed and named ai-engineering-from-scratch among their alternatives. The relationship is not symmetric — how ai-engineering-from-scratch rates them is a separate judgement, made when ai-engineering-from-scratch is analysed in its own right.

microsoft/generative-ai-for-beginnersGitHub

calls ai-engineering-from-scratch “Use when you prefer a from-scratch AI engineering curriculum that emphasizes building shipped applications.”

21 Lessons, Get Started Building with Generative AI

118.5kJupyter Notebookactive

dair-ai/Prompt-Engineering-GuideGitHub

calls ai-engineering-from-scratch “When you want a from-scratch curriculum for AI engineering including prompts and agents.”

🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

77.7kMDXactive

datawhalechina/hello-agentsGitHub

calls ai-engineering-from-scratch “If you prefer an English, MIT-licensed hands-on engineering course over the bilingual Datawhale book.”

📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程

74.2kPythonactive

bojieli/ai-agent-bookGitHub

calls ai-engineering-from-scratch “From-scratch AI engineering course, a peer educational resource.”

《深入理解 AI Agent：设计原理与工程实践》（李博杰著）开源主仓库：全书正文、编译版 PDF 与按章配套代码

40.8kPythonactive

patchy631/ai-engineering-hubGitHub

calls ai-engineering-from-scratch “Choose for a continuous from-scratch build-based tutorial series instead of a multi-project hub.”

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

37.5kJupyter Notebookactive

AMAI-GmbH/AI-Expert-RoadmapGitHub

calls ai-engineering-from-scratch “Choose if you want a current, from-scratch AI engineering roadmap with hands-on building rather than the seed's 2022 overview.”

Roadmap to becoming an Artificial Intelligence Expert in 2022

31.2kJavaScriptslowing

ZuzooVn/machine-learning-for-software-engineersGitHub

calls ai-engineering-from-scratch “Choose if you want a more recently maintained, project-driven AI learning path with the same hands-on approach.”

A complete daily plan for studying to become a machine learning engineer.

28.9kdormant

tangyudi/Ai-LearnGitHub

calls ai-engineering-from-scratch “Fresh, comprehensive AI engineering learning path in English; choose for a modern hands-on curriculum instead of the Chinese seed.”

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

13.3kdormant

didilili/ai-agents-from-zeroGitHub

calls ai-engineering-from-scratch “Choose it for an English-language, MIT-licensed curriculum; the seed is the better pick for Chinese-speaking readers who also want interview prep.”

🚀 2026 最系统的 AI Agent 速成指南｜智能体实战教程 · 完整学习路径 + 实战项目 + 面试题库 · 对标大模型应用开发工程师岗位 · 覆盖LangChain / LangGraph / Coze / Dify / MCP / skills / LLM / RAG / 提示词 · 企业级部署与微调 · 从0到企业级落地 + 从学习到上线项目 + 面试准备一体化

4.6kPythonactive

Snailclimb/AIGuideGitHub

calls ai-engineering-from-scratch “Choose it for an English-language, build-along curriculum when you want hands-on code over the seed's Chinese prose guide.”

AI 应用开发、AI 编程实战与面试指南，涵盖 LLM、Agent、RAG、MCP、Claude Code、Codex 等核心技术与工程实践。

611active

microsoft/AI-For-BeginnersGitHub

calls ai-engineering-from-scratch “choose it for a project-based engineering path in Python instead of the 12-week lesson-slide format; actively maintained.”

12 Weeks, 24 Lessons, AI for All!

68.5kJupyter Notebookactive

AccumulateMore/CV GitHub

calls ai-engineering-from-scratch “when you want a project-driven, build-and-ship approach to AI engineering over video-course notes.”

✅（已完结）超级全面的深度学习笔记【土堆 Pytorch】【李沐动手学深度学习】【吴恩达深度学习】【大飞大模型Agent】

23.7kJupyter Notebookactive

liyupi/ai-guideGitHub

calls ai-engineering-from-scratch “Project-based AI engineering path if you want to learn by building rather than browsing resources.”

程序员鱼皮的 AI 资源大全 + Vibe Coding 零基础教程，分享 OpenClaw 保姆级教程、大模型玩法（DeepSeek / GPT / Gemini / Claude / GLM）、最新 AI 资讯、Prompt 提示词大全、AI 知识百科（Agent Skills / RAG / MCP / A2A）、AI 编程教程（Harness Engineering）、AI 工具用法（Cursor / Claude Code / TRAE / Codex / Copilot）、AI 开发框架教程（Spring AI / LangChain）、AI 产品变现指南，帮你快速掌握 AI 技术，走在时代前沿。本项目为开源文档 aiguide，已升级为鱼皮 AI 导航网站

19.1kJavaScriptactive

adongwanai/AgentGuideGitHub

calls ai-engineering-from-scratch “Choose when you want a project-driven from-scratch AI engineering curriculum instead of a curated career guide.”

9.6kMDXactive

krishnaik06/The-Grand-Complete-Data-Science-MaterialsGitHub

calls ai-engineering-from-scratch “pick it for build-it-yourself AI engineering projects rather than lecture-style DS playlists”

9.1kPythondormant

HenryNdubuaku/maths-cs-ai-compendiumGitHub

calls ai-engineering-from-scratch “Use it when you want a Python build-and-ship AI-engineering curriculum instead of a reference-style compendium.”

Become a cracked AI/ML researcher/engineer with this unconventional textbook covering maths, computing, and ML with intuition.

7.4kTypeScriptactive

instillai/machine-learning-courseGitHub

calls ai-engineering-from-scratch “Choose when you want a hands-on AI/ML engineering path with project building rather than a broad algorithmic survey.”

:speech_balloon: Machine Learning Course with Python:

7.0kPythondormant

bryanyzhu/agentic-ai-system-courseGitHub

calls ai-engineering-from-scratch “choose when you want a broader AI-engineering-from-scratch curriculum rather than an agent-specific system design course”

Use agent to learn agent - A skeleton course on how to design, build, and operate production AI agents

611JavaScriptactive

Haozhe-Xing/agent_learningGitHub

calls ai-engineering-from-scratch “Choose it if you want a broader AI engineering curriculum rather than a dedicated agent-building textbook.”

A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch

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