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

LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.

Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs

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)

One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools.

Repositorio-Tutorial para desarrollo de chatbots, aplicaciones con LLMs y Agentes IA

Tutorial on how to create a ReAct agent without a LLM framework

🌍 The open-source Wikipedia of AI — 2M+ apps, agents, LLMs & datasets. Updated daily with tools, tutorials & news.

Hands-on tutorials for building AI agents from scratch. Learn LLM APIs, prompt engineering, tool calling, and the agent loop through practical examples.

Learn to build powerful AI agents from scratch. This repository contains tutorials, examples, and production-ready code for implementing intelligent automation with LLMs and multi-agent systems.

World-class deep-dive tutorials for open-source AI agents, vibe coding tools, LLM frameworks, and production systems.

Tutorials and exercises are done in the course 'Building RAG Agents with LLM'

Tutorial on LLMs and agents

LLM-RAG-Agent-Tutorial

Tutorial Materials for the paper "Evaluation & Benchmarking of LLM Agents: A Survey" published in KDD 2025 Conference.

A comprehensive guide and codebase for building AI agents with LLMs, featuring practical implementations from basic LLM interactions to complex multi-agent systems. Includes coding assistants, research agents, and step-by-step tutorials.

Repo containing artifacts for Neurips 2025 tutorial- How to Build Agents to Generate Kernels for Faster LLMs (and Other Models!)

Welcome to the Agentic AI Tutorial! This repository provides a step-by-step guide to creating agentic AI systems—intelligent agents that can reason, plan, and act autonomously using large language models (LLMs). Whether you're a beginner or an intermediate developer, this tutorial will take you from basic LLM calls to building a fully agent.

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

The "lcel-tutorial" repo is designed for mastering LangChain Expression Language (LCEL), offering exercises to build stateful, multi-actor LLM applications. It's a hands-on guide to leveraging LCEL for complex workflows and agent-like behaviors. Perfect for enthusiasts eager to explore LLM's potential.

欢迎来到 “LLM Tutorial 一起学大模型” GitHub 仓库！在这里，你将找到本系列课程的所有代码、文档和资源，涵盖大模型开发的核心主题。我们将重点探索 LangChain 和 LangGraph 框架，同时包括大模型微调、理论基础和 Agents 开发等内容。 无论你是初学者还是有经验的开发者，这里都是一个学习与分享的理想空间。欢迎大家下载、交流，和我一起在大模型的旅程中成长！ 如有任何问题或建议，欢迎在仓库中提交 issue 或 pull request，期待与你的互动！

Tutorials on building intelligent agents and autonomous workflows using LLMs. Learn to design and optimize AI-driven systems for real-world automation.

Code related to the PhaseLLM tutorial outlining how to extract structured data using Web Search Agents and LLMs.

Open-source guides and tutorials on AI agents, generative AI, and machine learning—covering Python, TypeScript, MCP server setup, MCP Clients, Ollama and LLM integration.

LLM Agent tutorials

Practical LLM Agent Tutorials for Absolute Beginners

This is a tutorial of an agentic Large Language Model (LLM) application to automate the evaluation of patients for clinical trials. It leverages documents related to patients' medical histories, clinical policies, and trial inclusion criteria.

Tutorial on builduing customer chatbot for coffee shop with Agent LLM and RAG

Tutorial on how to create LLM Agent using LangChain and Gemini

[2025.03.29] An AI bootcamp project with hands‑on tutorials in ML, LLMs, RAG, and AI agents