Advanced LangChain Techniques: Mastering RAG Applications
Advanced LangChain Techniques: Mastering RAG Applications, Elevate Your RAG Applications to the Next Level
Preview this Course
What you'll learn
- Learn LangChain Expression Language (LCEL)
- Master advanced RAG techniques using the LangChain framework
- Evaluate RAG pipelines using the RAGAS framework
- Apply NeMo Guardrails for safe and reliable AI interactions
Description
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! :-)
Who this course is for:
- Software Engineers and Data Scientists with Experience in Langchain who want to bring RAG applications to the next level
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