Build an Enterprise RAG System on AWS with Generative AI

About this course

This course contains the use of artificial intelligence.

Move beyond RAG concepts and build a complete enterprise AI system on AWS.In this hands-on course, you will build FinInsight, an end-to-end Retrieval-Augmented Generation (RAG) system that transforms financial documents into searchable knowledge and grounded AI answers.

Prior KnowledgeNo prior Cloud or AWS experience required.

No prior Python programming experience required.

No prior API testing or curl experience required.

We will work through what you need step by step.

What You Will BuildInstead of learning AWS and Generative AI services in isolation, you will see how they work together as part of a real application architecture.

Starting with a PDF document, you will build the workflow step by step: secure document intake, asynchronous text extraction, Generative AI analysis, customer matching, human confirmation, document archiving, knowledge enrichment, chunking, vector embeddings, vector indexing, semantic retrieval, grounded answer generation, and a conversational chat experience.

Along the way, you will work with services including Amazon Bedrock, Amazon Textract, AWS Lambda, Amazon S3, Amazon DynamoDB, Amazon API Gateway, Amazon EventBridge, and Amazon S3 Vectors.

You will also learn an AI-assisted development approach that connects business requirements to architecture, plain-English flows, Mermaid diagrams, implementation prompts, AI-generated Python code, AWS configuration, testing, and validation.

By the end of the course, you won't just understand how RAG works—you will understand how the surrounding cloud architecture turns RAG into a complete enterprise AI system.

You will learn not just what to build, but why each architectural decision matters.

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