Lordog / dive-into-llms
Chinese-language hands-on programming tutorial series on large language models, covering fine-tuning, prompting, editing, watermarking, jailbreaks, and agents.
Lordog / dive-into-llms
microsoft / ai-agents-for-beginners
An 18-lesson beginner course with code samples on building AI agents using Microsoft's agent frameworks and services.
AI4Finance-Foundation / FinRL
Open-source Python framework for training and backtesting financial trading agents with deep reinforcement learning.
datawhalechina / deepagents-in-action
📚 《Deep Agents 实战》—— LangChain 官方大使出品，基于 LangChain / LangGraph 生态，从零构建生产级 AI Agent 的完整指南
NirDiamant / GenAI_Agents
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
AccumulateMore / CV
✅（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】
alirezadir / AIMLInterviews
A study guide and interview-prep curriculum for AI/ML technical roles at big tech, covering coding, ML breadth, system design, and behavioral rounds.
patchy631 / ai-engineering-hub
A curated collection of tutorials and hands-on projects covering LLMs, RAG, and AI agent applications, organized by difficulty.
NirDiamant / agents-towards-production
Code-first Jupyter tutorials for building and deploying production-grade GenAI agents, from prototype to enterprise deployment.
xbsheng / atguigu-note
AI 课程笔记：langchain / langgraph / python / vibe coding
ed-donner / agents
Repo for the Complete Agentic AI Engineering Course
GiovanniPasq / agentic-rag-for-dummies
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
Akun-python / autumn-recruitment
Autumn-Recruit Algo Notes(秋招算法学习仓库)，面向大模型时代的算法、工程与AI学习共建仓库。从数学基础、数据结构，到机器学习、深度学习、LLM、Agent、AI-Infra、语音与数据科学，通过「理解→推导→手写 → 运行 → 验证 → 复盘构建可持续迭代的知识体系。
GoogleCloudPlatform / generative-ai
Sample notebooks, code, and apps demonstrating how to build with generative AI models on Google Cloud.
NirDiamant / Agent_Memory_Techniques
Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns.
hemansnation / AI-Engineer-Headquarters
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
microsoft / edgeai-for-beginners
This course is designed to guide beginners through the exciting world of Edge AI, covering fundamental concepts, popular models, inference techniques, device-specific applications, model optimization, and the development of intelligent Edge AI agents.
a2aproject / a2a-samples
Samples using the Agent2Agent (A2A) Protocol
benman1 / generative_ai_with_langchain
Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain.
calmrocks / ai-engineer-notebooks
Hands-on, framework-free Colab notebooks for the AI Engineer / Forward Deployed Engineer (FDE) skill set — model APIs, structured output, tool calling, RAG, evals-as-the-spine, agents (loop from scratch, tool design, guardrails, MCP, Skills), fine-tuning vs LoRA, prompt-injection/security, LLMOps, and customer craft. Runs on the free Groq API.
leoncuhk / awesome-quant-ai
A curated list of awesome resources for quantitative investment and trading strategies focusing on artificial intelligence and machine learning applications in finance.
oracle-devrel / oracle-ai-developer-hub
Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services
walkinglabs / self-improving-agent-notebook
Master self-improving LLM agents systematically with runnable Stanford CS329A notebooks.
zorost / AI-Engineering-Lab
A free, self-paced 24-week AI engineering course: Python, machine learning, LLMs, RAG, fine-tuning, agents and MCP, Azure and Vertex and Bedrock, and Databricks. 43 runnable notebooks, one continuous case study. MIT licensed, no signup. By Zorost Intelligence AI Lab.
Nicolepcx / harness_engineering
This is the corresponding code for the O'Reilly book: Harness Engineering
FareedKhan-dev / agentic-knowledge-graph
Knowledge-graph RAG built from structured metadata instead of LLM extraction. 929M edges, zero LLM calls, 83.2% on held-out PubMedQA. Case study: the full PubMed 2026 baseline.
RichmondAlake / agent_harness_course
Technical companion to the O'Reilly Harness Engineering for AI Agents workshop
mongodb-developer / GenAI-Showcase
MongoDB's Generative AI Showcase: an exhaustive collection of examples and sample applications covering Retrieval-Augmented Generation (RAG), AI agents, and industry-specific use cases.
MARKTECHPOST-AI-MEDIA-INC / AI-Agents-Projects-Tutorials
Multi-agent systems, memory, planning, reasoning loops
microsoft / CyberBattleSim
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
microsoft / TextWorld
TextWorld is a sandbox learning environment for the training and evaluation of reinforcement learning (RL) agents on text-based games.
towardsai / ragbook-notebooks
Repository for the "Building LLMs for Production" book by Towards AI.
deepset-ai / haystack-cookbook
👩🏻🍳 A collection of example notebooks using Haystack
Harrypatria / Agentic-AI-Masterclass-Handbook-Usecases-Convergeni
Building AI agents and retrieval systems, a masterclass in LLM agents, RAG, and production deployment.
GoogleCloudPlatform / asl-ml-immersion
Notebooks, code samples and reference for machine learning and generative ai on Google Cloud for the Advanced Solutions Lab (ASL) bootcamps.
onestardao / WFGY
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
curiousily / AI-Bootcamp
Self-paced bootcamp on Generative AI. Tutorials on ML fundamentals, Ollama, LLMs, RAGs, LangChain, LangGraph, Fine-tuning, DSPy & AI Agents (CrewAI), (Using ChatGPT, gpt-oss, Claude, Qwen, Gemma, Llama, Gemini)