AWS: Generative AI & Bedrock

This course is designed to provide a comprehensive introduction to Generative AI and the AWS services that enable organizations to build, customize, and deploy AI-powered applications. Learners will explore the foundational concepts of generative AI, understand how foundation models work, and discover how businesses are using these technologies to transform customer experiences, automate processes, and drive innovation. The course begins by introducing the core concepts of generative AI, including foundation models, model lifecycles, business use cases, challenges, and evaluation metrics. Learners will then explore Amazon Q and Amazon Bedrock, gaining an understanding of how AWS simplifies the development of generative AI applications through managed services and access to multiple foundation models. Finally, the course covers advanced concepts such as Retrieval-Augmented Generation (RAG), knowledge bases, AI agents, guardrails, and model evaluation, enabling learners to understand how modern AI applications are built and governed. This course is structured into multiple modules, each featuring lessons and video lectures that provide theoretical knowledge and practical demonstrations. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply generative AI concepts in real-world scenarios. Module 1: Generative AI Foundations Module 2: Amazon Q & Amazon Bedrock Fundamentals Module 3: RAG, Knowledge Bases & AI Agents ## At the end of the course, learners will learn * Understand the core concepts, terminology, use cases, and business value of Generative AI and Foundation Models. * Explore Amazon Q, Amazon Bedrock, and foundation model selection strategies to build AI-powered applications on AWS. * Understand Retrieval-Augmented Generation (RAG), knowledge bases, AI a