Learning Resources
Curated courses and hands-on tutorials — a deeper learning entry point beyond news and tools.
OpenMAIC - AI Multi-Agent Classroom
An open-source multi-agent platform that turns any topic or document into an interactive AI-taught lesson with slides, quizzes, and simulations.
Harness Engineering Learning Archive
An open-source research archive exploring harness engineering, where humans design constraints and AI agents execute, with curated articles and translations.
Deep Learning Book - Free PDF Guide
A free PDF covering deep learning fundamentals through advanced computer vision topics like detection, segmentation, and Vision Transformers.
Harvard CS197: AI Research Experiences
A free Harvard course book teaching the practical skills and methodology of doing AI research, from model fine-tuning to paper writing.
Bayesian Modeling and Computation in Python
A free online textbook teaching Bayesian statistical modeling and computation in Python with PyMC, ArviZ, and Bambi.
Learn Claude Code: Agent Harness Guide
A free 20-lesson course on building the tools, memory, permissions, and coordination infrastructure that turns an LLM into a reliable AI agent.
prompts.chat - Open-Source AI Prompt Library
A large open-source collection of ready-to-use prompts for ChatGPT, Claude, Gemini, and other AI models, plus a free prompt engineering guide.
Python-100-Days: Free Python Curriculum
A free 100-day, day-by-day curriculum on GitHub that takes beginners from Python basics to web development, databases, data analysis, and machine learning.
Dive into Deep Learning – Free D2L Textbook
A free interactive deep learning textbook combining theory, math, and runnable code in Jupyter notebooks, from fundamentals to advanced topics.
Prompt Engineering Guide
A comprehensive open-source guide covering prompting techniques, research, and applications for working effectively with large language models.
Hello-Agents - Build AI Agents from Scratch
An open-source Datawhale tutorial teaching how to build AI agents from scratch, covering LLM foundations, agent patterns, memory, and hands-on projects.
Generative AI for Developers Path
An advanced Google Skills learning path teaching developers, ML engineers, and data scientists how to build generative AI applications.
Foundations of LLMs - ZJU Open-Source Textbook
Open-source LLM textbook from Zhejiang University covering architecture, prompt engineering, fine-tuning, model editing, and RAG
Agentic Design Patterns - Complete Guide to 21 Design Patterns for Building Intelligent AI Agent Systems
A practical guide to AI agent system design patterns written by Google AI CTO, featuring 21 battle-tested design patterns covering the complete knowledge system from basic prompt chaining to advanced multi-agent collaboration
5-Day Intensive AI Agents Course – Free Online Course by Google & Kaggle
A 5-day intensive AI Agents course co-launched by Google and Kaggle, teaching how to build, evaluate, and deploy production-grade AI agent systems.
Vibe Coding in AI Studio – Hands-on Gemini API Tutorial
A hands-on tutorial on Vibe Coding in Google AI Studio, covering Gemini API, voice programming, tool integration, and rapid application development.
Understanding LLMs: The Technology Behind ChatGPT – Andrej Karpathy
Andrej Karpathy provides an in-depth explanation of large language model (LLM) technology, covering the complete training stack from fundamental neural networks to advanced models like GPT and Llama, including cutting-edge techniques such as RLHF (Reinforcement Learning from Human Feedback).
Stanford CS336: Language Modeling from Scratch | Complete Course on Building Language Models from Scratch
Stanford CS336 course, systematically explaining how to build a large language model from scratch, covering the complete process from data processing, Transformer architecture, model training, GPU optimization, parallel computing to RLHF alignment.
Agentic Design Patterns Chinese Translation - Complete Guide to 21 AI Agent Design Patterns
Chinese-English translation of Agentic Design Patterns, covering 21 AI agent design patterns, including core architectural methods such as prompt chaining, routing, and multi-agent collaboration, with Python code examples.
LLMs-from-scratch: Complete tutorial on building large language models from scratch
A complete tutorial on building large language models from scratch, implementing the GPT architecture step-by-step with PyTorch, including the entire process of pre-training, fine-tuning, and deployment.