Amazon Bedrock: Build GenAI Apps with RAG and Guardrails

About this course

Amazon Bedrock & Generative AI: Build AI Applications with RAG is a practical course designed to introduce learners to Amazon Bedrock and the core concepts required to build generative AI applications using foundation models and Retrieval-Augmented Generation (RAG). The course combines generative AI fundamentals with practical application concepts to help learners understand how modern AI solutions can retrieve relevant information and generate useful responses.

Please note, we have used AI-generated audio for this course to provide clear, consistent, and easy-to-follow narration throughout your learning journey.

The course begins with an introduction to generative AI, large language models, and foundation models. Learners will understand the role of foundation models in modern AI applications and how Amazon Bedrock provides access to generative AI capabilities through the AWS ecosystem.

Participants will explore Amazon Bedrock and its key capabilities for working with foundation models. They will develop an understanding of how different models can be evaluated and selected based on factors such as the application use case, expected output, performance, and resource requirements.

A major focus of the course is Retrieval-Augmented Generation (RAG). Learners will understand why traditional language models may not always have access to the most relevant or specialized information and how RAG can enhance AI applications by retrieving information from external knowledge sources before generating a response.

The course explores the key building blocks of a RAG workflow, including knowledge sources, document preparation, embeddings, vector representations, and information retrieval. Participants will understand how relevant information can be identified and provided to a generative AI model as additional context.

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