Welcome to this hands-on AI-900 lab session, where we explore Retrieval-Augmented Generation (RAG) with Azure AI Foundry! RAG enhances AI models by combining pre-trained generative AI with real-time data retrieval, allowing for more accurate, context-aware, and up-to-date responses. Whether you're preparing for the Microsoft AI-900 Certification or looking to build highly intelligent AI applications, this step-by-step tutorial will help you understand and implement RAG in Azure AI Foundry.<br /><br />🔍 What You’ll Learn in This Video:<br />1️⃣ Introduction to Retrieval-Augmented Generation (RAG) & Its Benefits<br />2️⃣ How RAG Improves AI Accuracy with Real-Time Data<br />3️⃣ Setting Up Azure AI Foundry for RAG Implementation<br />4️⃣ Integrating External Knowledge Sources with AI Models<br />5️⃣ Building a RAG Pipeline for AI-Driven Search & Question Answering<br />6️⃣ Optimizing & Deploying RAG-Enabled AI Models in Azure<br /><br />🛠️ Who Is This For?<br />AI & ML Enthusiasts exploring advanced AI techniques<br />Developers & data scientists working with AI-powered search & chatbots<br />Professionals preparing for the Microsoft AI-900 Certification<br />Businesses looking to enhance AI-driven applications with real-time information retrieval<br /><br />📌 Key Highlights:<br />✅ Hands-on demo of Retrieval-Augmented Generation (RAG) in Azure AI Foundry<br />✅ Enhancing AI models with external knowledge retrieval<br />✅ Optimizing AI for customer support, knowledge management, and enterprise search<br />✅ Deploying and testing RAG-powered AI applications<br /><br />rag in generative ai<br />how to implement rag in llm<br /><br />💡 Learn how to integrate real-time knowledge with AI models using Azure AI Foundry & RAG today!<br /><br />Explore our other Azure Courses and Practice Material on: https://www.youtube.com/@skilltechclub
