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Course
- AI
Evaluating RAG Solutions
Discover Retrieval Augmented Generation (RAG) for Developers. This course will teach you how to evaluate and implement RAG solutions to enhance the accuracy, efficiency, and relevance of information retrieval in AI applications.
What you'll learn
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.
Table of contents
About the author
Luca is an Automation Engineer who has been working for more than a decade on Linux Operating System and Open Source technologies. He has experience automating Tasks and Infrastructure using many technologies. For many years Luca has taught Linux at conferences and schools. He is currently working as an Ansible Technical Support Engineer for RedHat helping a huge variety of customers to automate their journey.
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