Welcome to the Generative AI Foundations module. In this module, you'll build a strong understanding of the core concepts behind Generative AI. We'll begin by exploring What is a Generative AI Model, along with key terminology, common use cases, challenges, and the major components that power generative AI systems. Next, you'll learn about the Lifecycle of Foundation Models, the different Types of Foundation Models, and how organizations select the right models for specific business needs. Finally, you'll explore Business Metrics for Generative AI, helping you understand how organizations measure the value, performance, and impact of AI initiatives. By the end of this module, you'll have a solid foundation in Generative AI concepts and be prepared to explore advanced AI services and applications.

Welcome to the Amazon Q & Amazon Bedrock Fundamentals module. In this module, you'll explore AWS's generative AI services and learn how organizations build AI-powered applications and assistants. You'll begin with Amazon Q Business, Amazon Q Apps, and Amazon Q Developer, understanding how these services help improve productivity, automate tasks, and accelerate software development. Next, you'll dive into Amazon Bedrock, starting with an overview and demo to understand how it provides access to leading foundation models through a fully managed service. You'll also learn how to choose the right foundation model for different business use cases. Finally, you'll explore foundation model fine-tuning, evaluation metrics, PartyRock - Amazon Bedrock Playground, and Amazon Bedrock pricing, helping you understand how to customize, evaluate, experiment with, and optimize AI solutions on AWS. By the end of this module, you'll have a solid understanding of Amazon Q, Amazon Bedrock, foundation models, and key considerations for building generative AI applications on AWS.

Welcome to the RAG, Knowledge Bases & AI Agents module. In this module, you'll explore how modern AI applications retrieve and use enterprise knowledge to generate more accurate and context-aware responses. You'll begin with Understanding RAG Architecture of LLMs and explore AWS Services for Storage of Vector Embeddings, learning how Retrieval Augmented Generation improves AI outputs using external knowledge sources. You'll then see these concepts in action through the Amazon Bedrock RAG & Knowledge Base Demo. Next, you'll learn how to implement responsible AI using Amazon Bedrock Guardrails, along with a hands-on demo to understand safety controls, content filtering, and governance capabilities. Finally, you'll explore Amazon Bedrock Agents, model evaluation techniques, and integrations with services such as Amazon S3 and Amazon CloudWatch, helping you understand how intelligent agents can automate workflows and interact with enterprise systems. By the end of this module, you'll understand how to build secure, scalable, and knowledge-driven AI solutions using Amazon Bedrock.