AWS Certified Generative AI Developer – Professional Exam Prep and Study Guide | Course Playlist - Setting Up RAG with Amazon Bedrock | Set Up Amazon OpenSearch for Vector Storage | RAG Tutorial

Learn how to build a Retrieval-Augmented Generation (RAG) system and Knowledge Base using Amazon Bedrock! In this hands-on tutorial, we walk you through the entire process of setting up a fully functional RAG pipeline, including: ✅ Creating an IAM User for secure access ✅ Setting up a Knowledge Base in Amazon Bedrock ✅ Creating and configuring an Amazon S3 Bucket for document storage ✅ Connecting Amazon S3 to Bedrock for data ingestion ✅ Using Amazon Titan Text Embeddings V2 for vectorization ✅ Setting up Amazon OpenSearch Serverless for vector storage ✅ Syncing data and testing with Anthropic Claude Haiku/Sonnet ✅ Cleaning up resources to avoid unexpected costs 📌 By the end of this tutorial, you’ll have a fully operational RAG system that retrieves information from a knowledge base to enhance AI responses! 🔗 Resources & Links: 📄 AWS Bedrock Docs: https://aws.amazon.com/bedrock/ 📂 OpenSearch Pricing: https://aws.amazon.com/opensearch-service/pricing/ 🔍 Pinecone (Alternative Vector Store): https://www.pinecone.io KnoDAX books related to AWS Certified AI Practitioner exam: AWS Certified AI Practitioner Exam Prep and Study Guide: Comprehensive Coverage of all Exam Domains | 3 Full-length Practice Tests with Answer Analysis | Exam Key Points | Lab Exercises: https://www.amazon.com/dp/B0DZTXPK2P AWS Certified AI Practitioner Exam Notes & Practice Tests: 8 Full-Length Practice Exams with Answer Analysis | 500+ Practice Questions | Key Exam Notes: https://www.amazon.com/dp/B0DZW89V2B ⚡ Don't forget to like, share, and subscribe for more hands-on AWS tutorials! #AWS #AmazonBedrock #MachineLearning #RAG #AI #CloudComputing #OpenSearch #KnowledgeBase