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Master the art of evaluating Retrieval-Augmented Generation (RAG) systems with the most practical and complete course on the market — trusted by over 25,000 students and backed by 1,000+ 5-star reviews.
Whether you're building LLM applications, leading AI QA efforts, or shipping reliable MVPs, this course gives you all the tools, code, and frameworks to test and validate RAG pipelines using DeepEval and RAGAS. What You’ll Learn Understand the Basics of LLMs and how they are applied across industriesExplore different LLM Application Types and use casesLearn the difference between Weak AI and Generative AIDeep-dive into how RAG works, and where testing fits into the pipelineDiscover the types of RAG Testing: factuality, hallucination detection, context evaluation, etc.Get hands-on with ready-to-use code from Day 0 — minimal setup requiredMaster classic ML metrics (Accuracy, Recall, F1) and where they still matterLearn RAG-specific metrics:Context RecallContext AccuracyAnswer RelevancyTruthfulnessFluency, Coherence, Tone, ConcisenessBuild custom test cases and metrics with DeepEval and RAGASLearn how to use RAGAS and DeepEval open-source frameworks for production and researchValidate MVPs quickly and reliably using automated test coverage Who is This For? AI & LLM Developers who want to ship trustworthy RAG systemsQA Engineers transitioning into AI testing rolesML Researchers aiming for reproducible benchmarksProduct Managers who want to measure quality in RAG outputsMLOps/DevOps professionals looking to automate evaluation in CI/CD Who this course is for: AI Engineers & LLM DevelopersQA/Test Automation Engineers transitioning to AIML Researchers & Applied ScientistsAI Product Managers
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