Apr 10
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Learn how to build real-world AI applications using Retrieval Augmented Generation (RAG) with Azure AI Search and OpenAI. In this video, we go beyond theory and implement a complete RAG pipeline — from user query to contextual AI response using vector search and embeddings. 🔹 What you’ll learn: - What is RAG (Retrieval Augmented Generation) - Grounding vs Ungrounded AI responses - How RAG improves LLM accuracy - Azure AI Search integration - Vector database & embeddings explained - End-to-end RAG architecture - Real-world use cases 🔹 Technologies covered: - Azure AI Search - OpenAI / Azure OpenAI - Vector Search (Embeddings) - CLIP Model (Image & Text Embeddings)- This video is perfect for: - AI Engineers - Developers building AI apps - Students preparing for AI-102 - Anyone working with ChatGPT / LLMs 𝐖𝐚𝐭𝐜𝐡 𝐅𝐑𝐄𝐄 𝐯𝐢𝐝𝐞𝐨 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: https://tinyurl.com/bestitcourses-tutorials Join Our AI for Developers Whatsapp Community for FREE Webinars ,Tech Updates , Tips and many more: https://tinyurl.com/42y858sr #bestitcourses #deccansoft #bestdotnettraining #Sandeepsoni 📲 Connect with me 👋 Connect with me on LINKEDIN ► https://www.linkedin.com/in/sandeepsoni123/ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Please do subscribe so we reach our goal faster :) https://www.youtube.com/user/Deccansoft123 👨🏻🏫 This complete tutorial is compiled by Sandeep Soni, a Microsoft Certified Trainer, a Software & Corporate Trainer for 27years! For more information of this course, check out our Website: https://www.bestitcourses.com