🚀 Large Language Models Tutorial Collection

Master LLMs with 30+ hands-on tutorials - From basic concepts to advanced AI agents, all with practical Jupyter notebooks you can run instantly.

🎯 What You'll Learn

Transform from LLM beginner to expert with interactive tutorials covering:

• 🧠 Core Concepts: Embeddings, Vector Stores, Prompt Engineering
• 🔗 LangChain Mastery: Chains, Agents, Memory, and Tools
• 🤖 AI Applications: Chatbots, Q&A Systems, Content Generation
• 🛠️ Advanced Techniques: RAG, Function Calling, Multi-Agent Systems
• 🔍 Specialized Use Cases: Speech Recognition, Image Generation, Research Agents

🚀 Quick Start

Option 1: Run in Google Colab (Recommended)

No setup required! Click above to start learning immediately.

Option 2: Local Installation

# Clone the repository
git clone https://github.com/atef-ataya/Large-Language-Models-Tutorial.git
cd Large-Language-Models-Tutorial

# Install dependencies
pip install -r requirements.txt

# Start Jupyter
jupyter notebook

Option 3: GitHub Codespaces

📚 Tutorial Catalog

🎓 Beginner Tutorials

Tutorial	Description	Colab Link
LangChain 101	Master embeddings, vector stores, and retrieval
Prompt Engineering	Learn advanced prompting techniques
Zero-Shot Sentiment Analysis	Classify text without training data

🛠️ Application Development

Tutorial	Description	Colab Link
Question-Answering System	Build intelligent Q&A applications
ChatGPT Clone	Create your own conversational AI
Wikipedia Chatbot	OpenAI + Pinecone powered chatbot

🤖 AI Agents & Advanced Techniques

Tutorial	Description	Colab Link
Tavily AI Research Agent	Autonomous research and analysis
Multi-Agent Systems	Coordinate multiple AI agents
LangGraph Workflows	Build complex AI workflows

🎨 Creative & Specialized Applications

Tutorial	Description	Colab Link
Recipe & Image Generator	AI-powered cooking assistant
Speech Recognition	Whisper-powered voice interfaces
YouTube Summarizer	Extract insights from videos

🎥 Video Tutorials

Each notebook corresponds to a detailed video tutorial on my YouTube channel:

Latest Videos:

• 🎬 Building AI Agents with LangGraph
• 🎬 Advanced Prompt Engineering Techniques
• 🎬 Creating Production-Ready LLM Applications

🛠️ Prerequisites

• Python 3.8+
• Basic Python knowledge
• Jupyter Notebook (or use Colab)
• API Keys for OpenAI, Pinecone, etc. (instructions in each notebook)

💡 Key Features

• ✅ 30+ Interactive Notebooks - Hands-on learning with real code
• ✅ Production-Ready Examples - Not just toy projects
• ✅ Clear Documentation - Every step explained
• ✅ Regular Updates - New tutorials added monthly
• ✅ Community Support - Active discussions and help
• ✅ Multiple Deployment Options - Colab, local, or Codespaces

🚀 Getting Started Guide

1. Choose Your Path: Pick Colab for instant access or local setup for full control
2. Start with Basics: Begin with "LangChain 101" if you're new to LLMs
3. Follow Along: Each notebook includes video explanations
4. Experiment: Modify code and parameters to see what happens
5. Build Projects: Use tutorials as foundation for your own applications

🤝 Contributing

Love this project? Here's how you can help:

• ⭐ Star this repository if it helps you learn
• 🍴 Fork and contribute your own tutorials
• 🐛 Report issues or suggest improvements
• 📢 Share with others who might find it useful

Contributing Guidelines

• Check out our Contributing Guide
• Look for good first issues
• Join our Discussions

📊 Project Stats

🌟 Community

Join our growing community of LLM enthusiasts:

• 💬 GitHub Discussions - Ask questions and share ideas
• 🐦 Twitter - Latest updates and AI insights
• 🌐 Personal Website - Blog posts and additional resources
• 📺 YouTube - Video tutorials and explanations

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• OpenAI for GPT models and API
• LangChain for the amazing framework
• Jupyter for the interactive notebook experience
• The Community for feedback and contributions

🔮 Roadmap

Coming Soon

• Advanced RAG techniques
• Multi-modal AI applications
• LLM fine-tuning tutorials
• Production deployment guides
• API integration examples

Want to Suggest a Tutorial?

Open an issue with your idea!

⭐ Found this helpful? Give it a star and share with fellow developers!

Built with ❤️ by Atef Ataya | Follow me on Twitter for AI updates