Master LLMs with 30+ hands-on tutorials - From basic concepts to advanced AI agents, all with practical Jupyter notebooks you can run instantly.
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
No setup required! Click above to start learning immediately.
# 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
| 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 | |
| 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 | |
| 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 | |
| Tutorial | Description | Colab Link |
|---|---|---|
| Recipe & Image Generator | AI-powered cooking assistant | |
| Speech Recognition | Whisper-powered voice interfaces | |
| YouTube Summarizer | Extract insights from videos | |
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
- Python 3.8+
- Basic Python knowledge
- Jupyter Notebook (or use Colab)
- API Keys for OpenAI, Pinecone, etc. (instructions in each notebook)
- ✅ 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
- Choose Your Path: Pick Colab for instant access or local setup for full control
- Start with Basics: Begin with "LangChain 101" if you're new to LLMs
- Follow Along: Each notebook includes video explanations
- Experiment: Modify code and parameters to see what happens
- Build Projects: Use tutorials as foundation for your own applications
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
- Check out our Contributing Guide
- Look for good first issues
- Join our Discussions
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
This project is licensed under the MIT License - see the LICENSE file for details.
- OpenAI for GPT models and API
- LangChain for the amazing framework
- Jupyter for the interactive notebook experience
- The Community for feedback and contributions
- Advanced RAG techniques
- Multi-modal AI applications
- LLM fine-tuning tutorials
- Production deployment guides
- API integration examples
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