RAGAS Tutorial | Eval-Driven Development for RAG Systems | AI Evaluation, Hallucination Detection & Response Quality Metrics

Building a RAG application is only the beginning. The real challenge is proving that your AI is accurate, reliable, and free from hallucinations.

In this lesson of Phase 5 (Eval-Driven RAG Systems) from the AI Engineer 360 course, you'll learn how professional AI Engineers use RAGAS to evaluate retrieval quality, measure hallucinations, analyse response quality, and continuously improve production AI systems.

What You'll Learn
What AI Evaluation is
Eval-Driven Development (Build → Test → Evaluate → Improve)
RAGAS Framework Explained
Evaluation Pipelines
Hallucination Detection & Scoring
Faithfulness, Answer Relevancy, Context Precision & Context Recall
Response Quality Metrics
Enterprise AI Evaluation Best Practices

This lesson transforms your RAG application from "it works" to "we can prove it works."

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