Descriptions
Advanced LangChain Techniques: Mastering RAG Applications, Welcome to the Advanced Retrieval-Augmented Generation (RAG) course with the LangChain Framework! In this course, you will master advanced RAG techniques, leveraging the open-source LangChain framework to connect large language models (LLMs) with essential components for powerful AI-driven language tasks. You will gain a deep understanding of RAG, from foundational concepts to advanced implementations, including LCEL, chat with history, indexing APIs, evaluation tools, chunking, embedding models, query formulation, reranking, routing, agents, tool calling, NeMo Guardrails, and Langfuse integration.
The course is designed for developers, software engineers, and data scientists with experience in LLMs and LangChain. You will also access helper scripts for data ingestion and cleanup, and build a full-stack chatbot app with React and FastAPI, complete with Docker support. By the end, you will be equipped to build, evaluate, and deploy advanced RAG applications with confidence.
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
Who this course is for
- Software Engineers and Data Scientists with Experience in Langchain who want to bring RAG applications to the next level
Specificatoin of Advanced LangChain Techniques: Mastering RAG Applications
- Publisher : Udemy
- Teacher : Markus Lang
- Language : English
- Level : Intermediate
- Number of Course : 37
- Duration : 3 hours and 31 minutes
Content of Advanced LangChain Techniques: Mastering RAG Applications
Requirements
- LangChain Basics
- Intermediate Python Skills (OOP, Datatypes, Functions, modules etc.)
- Basic Terminal and Docker knowledge
Pictures
Sample Clip
Installation Guide
Extract the files and watch with your favorite player
Subtitle : English
Quality: 720
Download Links
Password file(s): www.downloadly.ir
File size
1.86 GB
