Advanced LangChain Techniques: Mastering RAG Applications | Udemy

What to Expect from This Course

Welcome to our course on Advanced Retrieval-Augmented Generation (RAG) with the LangChain Framework!

In this course, we dive into advanced techniques for Retrieval-Augmented Generation, leveraging the powerful LangChain framework to enhance your AI-powered language tasks. LangChain is an open-source tool that connects large language models (LLMs) with other components, making it an essential resource for developers and data scientists working with AI.

Course Highlights

Focus on RAG Techniques: This course provides a deep understanding of Retrieval-Augmented Generation, guiding you through the intricacies of the LangChain framework. We cover a range of topics from basic concepts to advanced implementations, ensuring you gain comprehensive knowledge.

Comprehensive Content: The course is designed for developers, software engineers, and data scientists with some experience in the world of LLMs and LangChain. Throughout the course, you’ll explore:

• LCEL Deepdive and Runnables
• Chat with History
• Indexing API
• RAG Evaluation Tools
• Advanced Chunking Techniques
• Other Embedding Models
• Query Formulation and Retrieval
• Cross-Encoder Reranking
• Routing
• Agents
• Tool Calling
• NeMo Guardrails
• Langfuse Integration

Additional Resources

• Helper Scripts: Scripts for data ingestion, inspection, and cleanup to streamline your workflow.
• Full-Stack App and Docker: A comprehensive chatbot application with a React frontend and FastAPI backend, complete with Docker support for easy setup and deployment.
• Additional resources are available to support your learning.

Happy Learning! 🙂