What is RAG? Retrieval-Augmented Generation Explained | Azure AI-901 Certification | Day 7

🚀 DAY 7 | What is RAG? Retrieval-Augmented Generation Explained | Azure AI-901 Welcome to DAY 7 of the Microsoft Azure AI Fundamentals (AI-901) Complete Course Series on TechVerse with Suraj. In this lesson, we break down Retrieval-Augmented Generation (RAG) from the ground up and explain how RAG helps generative AI applications provide answers using relevant external information. If you're preparing for the Microsoft AI-901 Azure AI Fundamentals certification, learning Generative AI, or working toward an AI/Cloud career, this lesson will help you understand the RAG lifecycle in a simple and practical way. 🔥 WHAT YOU'LL LEARN ✅ What is RAG (Retrieval-Augmented Generation)? ✅ Why RAG is useful for Generative AI applications ✅ RAG vs Model Memory ✅ How to prepare data for RAG ✅ Data cleaning and chunking ✅ Why chunking matters ✅ Indexing data for efficient retrieval ✅ How RAG retrieves relevant information ✅ Ranking and selecting relevant content ✅ Grounding an AI model with retrieved context ✅ How the model generates a grounded response ✅ RAG quality and common failure scenarios ✅ How to evaluate a RAG solution ✅ Retrieval quality vs generated answer quality ✅ RAG vs Fine-Tuning ✅ When to use RAG for changing or private information ✅ RAG in a real-world company chatbot ✅ RAG + AI Agents ✅ Azure perspective for AI-901 ✅ AI-901 exam-focused RAG concepts 📚 RAG LIFECYCLE