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Evaluating Large Language Model (LLM) applications is critical to ensuring reliability, accuracy, and user trust—especially as these systems are integrated into real-world solutions. This hands-on course guides you through the complete evaluation lifecycle of LLM-based applications, with a special focus on Retrieval-Augmented Generation (RAG) and Agentic AI workflows.
You'll begin by understanding the core evaluation process, exploring how to measure quality across different stages of a RAG pipeline. Dive deep into RAGAs—the community-driven evaluation framework—and learn to compute key metrics like context relevancy, faithfulness, and hallucination rate using open-source tools.
Through practical labs, you'll create and automate tests with Pytest, evaluate multi-agent systems, and implement tests using DeepEval. You'll also trace and debug your LLM workflows with LangSmith, gaining visibility into each component of your RAG or Agentic AI system.
By the end of the course, you’ll know how to create custom evaluation datasets and validate LLM outputs against ground truth responses. Whether you're a developer, quality engineer, or AI enthusiast, this course will equip you with the practical tools and techniques needed to build trustworthy, production-ready LLM applications.
No prior experience in evaluation frameworks is required—just basic Python knowledge and a curiosity to explore.
Enroll and learn how to evaluate or test Gen AI application.
Everything You Need to Know About How to test or Evaluate Gen AI, LLM, RAG, Agentic AI
This course is a comprehensive and well-structured introduction to How to test or Evaluate Gen AI, LLM, RAG, Agentic AI. The instructor, Soumen Kumar Mondal, is a leading expert in the field with a wealth of experience in IT & Software to share.
The course is well-structured and easy to follow, and the instructor does a great job of explaining complex concepts in a clear and concise way.
The course is divided into sections, each of which covers a different aspect related to Other IT & Software. Each module contains a series of video lectures, readings, and hands-on exercises.
The instructor does a great job of explaining each topic in a clear and concise way. He/She also provides plenty of examples and exercises to help students learn the material.
One of the things I liked most about this course is that it is very practical. The instructor focuses on teaching students the skills and knowledge they need to succeed in the real world. He/She also provides students with access to a variety of resources, including templates, checklists, and cheat sheets.
Another thing I liked about this course is that it is offered on Udemy. Udemy is a great platform for taking online courses because it offers a lot of flexibility for students. Students can choose to take courses at their own pace, and they can access the course materials from anywhere with an internet connection.
Udemy also offers a variety of payment options, so students can find a plan that works for them. The course also has a very active community forum where students can ask questions and interact with each other. The instructor is also very responsive to student questions and feedback.
Overall, I highly recommend this course to anyone who is interested in learning How to test or Evaluate Gen AI, LLM, RAG, Agentic AI. It is a well-organized and informative course that will teach you the skills and knowledge you need to succeed.
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