Current customer support systems often struggle to provide quick and accurate responses to user queries, especially those requiring specific, contextually relevant information from a vast knowledge base. In this course, Evaluating RAG Solutions, you’ll learn to implement and optimize Retrieval Augmented Generation (RAG) systems. First, you’ll explore how to identify the specific needs and requirements for an effective RAG system. Next, you’ll discover how to evaluate and select the most suitable RAG model based on performance metrics. Finally, you’ll learn how to set up, configure, test, and optimize the RAG system for deployment. When you’re finished with this course, you’ll have the skills and knowledge of RAG solutions needed to enhance the accuracy, efficiency, and relevance of information retrieval in AI applications.
Overview
Current customer support systems often struggle to provide quick and accurate responses to user queries, especially those requiring specific, contextually relevant information from a vast knowledge base. In this course, Evaluating RAG Solutions, you’ll learn to implement and optimize Retrieval Augmented Generation (RAG) systems. First, you’ll explore how to identify the specific needs and requirements for an effective RAG system. Next, you’ll discover how to evaluate and select the most suitable RAG model based on performance metrics. Finally, you’ll learn how to set up, configure, test, and optimize the RAG system for deployment. When you’re finished with this course, you’ll have the skills and knowledge of RAG solutions needed to enhance the accuracy, efficiency, and relevance of information retrieval in AI applications.
Syllabus
- Evaluating RAG Solutions 19mins
Taught by
Luca Berton