Retrieval Augmented Generation

Embark on a 6-day live training journey to learn the fundamentals of Retrieval-Augmented Generation (RAG) using Langchain. This introductory training provides a practical and hands-on approach to understanding the core components and workflows involved in RAG development. 

What You Will Learn: 

Module 1: End-to-End Simple RAG

Start with the basics by building a simple RAG system from scratch. This module provides an overview of the RAG framework and walks you through the end-to-end process, setting the foundation for more advanced topics. 

Module 2: Query Translation & Routing

Learn how to translate user queries into actionable tasks for your RAG system. Understand the importance of query routing and how to direct queries to the appropriate resources for optimal results. 

Module 3: Query Construction & Indexing

Dive into constructing effective queries that enhance the retrieval process. Explore indexing techniques to organize and manage your data, ensuring efficient and accurate information retrieval. 

Module 4: Retrieval & Generation

Master the retrieval process by learning to fetch relevant information based on user queries. Discover the generation phase, where the retrieved data is transformed into coherent and useful responses. 

Module 5: RAG Evaluation

Understand how to evaluate your RAG system’s performance. Learn key metrics and evaluation techniques to ensure your system delivers accurate and valuable outputs. 

Pre-requisites: 

• Basic understanding of Python programming 
• Familiarity with natural language processing (NLP) concepts 
• No prior experience with Langchain is required