Awesome AI Agents › Courses and Tutorials
A comprehensive guide and resource hub for prompt engineering, context engineering, retrieval-augmented generation, and AI agents, offering tutorials, papers, tools, and courses to optimize the use of large language models.
Learn Claude Code is an educational project that teaches how to build modern AI coding agents like Claude Code through a progressive tutorial covering core concepts, planning, subagents, and skills mechanisms.
AI Engineering Hub is a comprehensive repository offering in-depth tutorials and practical resources on Large Language Models, Retrieval-Augmented Generation, and real-world AI agent applications for learners and practitioners.
The Hugging Face Agents Course is a comprehensive educational resource that teaches the fundamentals and advanced concepts of AI agents and large language models through structured units, practical frameworks, and community collaboration.
GenAI_Agents is a comprehensive repository offering tutorials, implementations, and community resources for building and advancing generative AI agents from basic to advanced levels.
This course provides a comprehensive project-based tutorial on Harness Engineering for building reliable AI coding agents, covering environment setup, state management, verification, and control.
An AI-powered tool that analyzes GitHub repositories and generates beginner-friendly tutorials with visualizations to simplify understanding complex codebases.
A comprehensive guide to prepare for machine learning and AI technical interviews at major tech companies, covering coding, ML fundamentals, system design, and behavioral aspects.
A trilingual (Traditional Chinese, English, Simplified Chinese) learning roadmap for agentic AI, offering 240+ curated resources and hands-on examples from LLM basics to multi-agent systems.
The AI Cookbook by Dave Ebbelaar offers practical examples and tutorials with copy/paste code snippets to help developers build real-world AI systems efficiently.
Tutorial and modular reference implementation of an agentic RAG system on LangGraph, covering hierarchical indexing, conversation memory, query clarification and multi-agent map-reduce retrieval.
A comprehensive curated list of resources for game development, covering topics from game engines and assets to graphics, physics, and AI.
Educational reverse-engineering notes on the architecture of Claude Code, covering the agent loop, context engineering, tool system, skills, memory and the layered permission model across 16+ documents.
Microsoft repository hosting the Copilot Studio Agent Academy, a three-part course with mission-based lessons for people who want to build agents with Microsoft Copilot Studio.
An open-source course teaching how to build a production-ready Second Brain AI assistant using LLMs, RAG, agents, fine-tuning, and LLMOps with practical system design and deployment techniques.
A comprehensive resource hub for learning Generative AI, including roadmaps, projects, use cases, interview and coding preparation, and cloud deployment guides.
Ava is a comprehensive course and project for building a production-ready AI WhatsApp agent capable of realistic conversations, voice and image recognition, and deployment using advanced AI technologies and cloud services.
Companion repository for a LangChain and LangGraph course that teaches AI agent development through seven progressively harder Python projects spread across git branches and linked repositories.
Educational JavaScript repository that builds retrieval-augmented generation from first principles in ordered, self-contained examples running locally with no cloud APIs or framework abstractions.
A free cohort-based course on AI-native software engineering, teaching disciplined use of AI coding tools and agents for building, testing, deploying and auditing real applications.
PhiloAgents Course is an open-source educational project that teaches how to build an AI-powered game simulation engine impersonating historical philosophers, combining philosophy with modern AI technology through hands-on modules covering agent development, RAG systems, system architecture, and LLMOps best practices.
Companion code repository for the book "Generative AI with LangChain, 2024 Edition," providing practical examples and resources to build large language model applications using LangChain and Python.
Code repository for the book Designing Multi-Agent Systems, containing PicoAgents, a complete multi-agent framework written from scratch to teach agent reasoning loops, orchestration patterns and evaluation.
Collection of 80+ self-contained, runnable Python examples for building autonomous and multi-agent systems with Fetch.ai uAgents, ASI:One, Agentverse, MCP, A2A and mainstream LLM SDKs.
Agent Memory Techniques is a tutorial repository of 30 runnable Jupyter notebooks covering memory patterns for LLM agents, from conversation buffers to knowledge graphs, MemGPT, Mem0, Letta, Zep and Graphiti.
Educational repository that builds a single AI agent step by step across twelve lessons using a local GGUF model, with no frameworks, no cloud APIs and no hidden reasoning.
Self-paced bootcamp of Jupyter notebooks and tutorials covering machine learning foundations, MLOps, local LLMs with Ollama, RAG, LangChain, LangGraph, DSPy, fine-tuning and CrewAI agents.
Official example repository for the Strands Agents SDK, with Python and TypeScript tutorials covering agent fundamentals, multi-agent systems, deployment, integrations, evaluation and industry use cases.
Curated repository of complete, runnable AI agent and LLM application examples grouped into starter agents, advanced agents, multi-agent teams, RAG applications and multimodal apps across many frameworks and model providers.
A documentation-only English playbook on earning money with AI-assisted "vibecoding", covering coding agents, MCP servers, prompting workflow, delivery process and a Cloudflare-based stack.
Open course that walks through building Kubrick, a multimodal video-processing agent, covering a FastMCP server over Pixeltable, a custom MCP client, a Groq-hosted Llama 4 agent and Opik tracing.
A comprehensive collection of Jupyter notebooks supporting the "Building LLMs for Production" book, covering foundational concepts, advanced techniques, and practical applications of large language models in production environments.
Practical handbook for building, evaluating, securing and shipping LLM agent systems, covering the whole agent stack with adapters for 24 or more providers, blueprints, templates and checklists.
Guide and companion configuration kit for Claude Code, shipping a global CLAUDE.md template, hook scripts, skills and a settings template; the authors mark this version obsolete in favour of a newer starter kit.
Agentic-AI-Systems is a structured learning repository on building production agentic systems, combining notes on foundations, framework tutorials, design patterns, use cases and interview preparation material.
A documented methodology with reusable prompt and persona files for working with AI models on software projects, using file size limits, phased planning and validation gates to curb code bloat and context drift.
Claude-React-Jumpstart is a beginner-friendly step-by-step tutorial for setting up and running Claude-generated React code locally using Vite, Tailwind CSS, and Shadcn UI components.