In Week 2, we’ll shift our focus to Retrieval-Augmented Generation (RAG), safety mechanisms, and agent-based orchestration in Amazon Bedrock. You’ll begin by understanding the architecture and principles behind RAG and how it enhances large language model (LLM) outputs with external knowledge sources. This week also introduces you to Amazon Bedrock Guardrails—a powerful toolset for implementing content safety, privacy filters, and responsible AI controls. You’ll explore how to create and apply Guardrails through practical demos. Finally, you’ll get hands-on with Bedrock Agents, learning how to configure them to automate workflows, enhance interactivity, and support dynamic, multi-step tasks. By the end of this module, you’ll be equipped to build secure, reliable, and intelligent generative AI applications using Amazon Bedrock’s advanced capabilities.

Welcome to Week 3! This final module focuses on advanced topics including workflow automation, system integration, and career development within the Amazon Bedrock ecosystem. You’ll learn how to streamline generative AI processes using Amazon Bedrock Flows and implement data-driven automation through Bedrock Data Automation (BDA). We’ll also explore how to monitor and integrate Bedrock applications with AWS services like Amazon CloudWatch and Amazon S3 to ensure operational visibility and performance. Finally, you’ll gain insight into the certifications, career paths, and job opportunities available for professionals working with generative AI and AWS technologies. By the end of the week, you’ll be equipped with the skills to automate, monitor, and scale generative AI solutions—while confidently navigating your career journey in the AWS ecosystem.