
Learn the complete way to test RAG implementations. From functional to performance from Python to RAGAs and DeepEval
Course Description
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 industries
Explore different LLM Application Types and use cases
Learn the difference between Weak AI and Generative AI
Deep-dive into how RAG works, and where testing fits into the pipeline
Discover the types of RAG Testing: factuality, hallucination detection, context evaluation, etc.
Get hands-on with ready-to-use code from Day 0 — minimal setup required
Master classic ML metrics (Accuracy, Recall, F1) and where they still matter
Learn RAG-specific metrics:
Context Recall
Context Accuracy
Answer Relevancy
Truthfulness
Fluency, Coherence, Tone, Conciseness
Build custom test cases and metrics with DeepEval and RAGAS
Learn how to use RAGAS and DeepEval open-source frameworks for production and research
Validate MVPs quickly and reliably using automated test coverage
Understand the Basics of LLMs and how they are applied across industries
Explore different LLM Application Types and use cases
Learn the difference between Weak AI and Generative AI
Deep-dive into how RAG works, and where testing fits into the pipeline
Discover the types of RAG Testing: factuality, hallucination detection, context evaluation, etc.
Get hands-on with ready-to-use code from Day 0 — minimal setup required
Master classic ML metrics (Accuracy, Recall, F1) and where they still matter
Learn RAG-specific metrics:
Context Recall
Context Accuracy
Answer Relevancy
Truthfulness
Fluency, Coherence, Tone, Conciseness
Context Recall
Context Accuracy
Answer Relevancy
Truthfulness
Fluency, Coherence, Tone, Conciseness
Build custom test cases and metrics with DeepEval and RAGAS
Learn how to use RAGAS and DeepEval open-source frameworks for production and research
Validate MVPs quickly and reliably using automated test coverage
Who is This For?
AI & LLM Developers who want to ship trustworthy RAG systems
QA Engineers transitioning into AI testing roles
ML Researchers aiming for reproducible benchmarks
Product Managers who want to measure quality in RAG outputs
MLOps/DevOps professionals looking to automate evaluation in CI/CD
AI & LLM Developers who want to ship trustworthy RAG systems
QA Engineers transitioning into AI testing roles
ML Researchers aiming for reproducible benchmarks
Product Managers who want to measure quality in RAG outputs
MLOps/DevOps professionals looking to automate evaluation in CI/CD

