Overview

e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming.Step up your generative AI skills with this course focused on building generative AI applications using Amazon Bedrock. Building on the fundamentals, you'll dive deep into advanced features and services that enable more complex solutions. The course begins with a deep dive of Amazon Bedrock Knowledge Bases, teaching you how to enhance AI responses using Retrieval-Augmented Generation (RAG). You'll learn to create and manage knowledge bases, integrating them into your applications to provide context-aware, domain-specific AI interactions. Next, you'll learn Amazon Bedrock Prompt Management and Flows, enabling you to design intricate workflows that chain multiple AI operations. This section empowers you to create more sophisticated generative AI behaviors in your applications.The latter part of the course focuses on generative AI-driven agents for task automation. You'll learn to configure and deploy Bedrock Agents, integrating them with various AWS services to create smart, autonomous systems. You'll also explore the Converse API, enabling more natural, context-aware conversations in your AI applications. Throughout the course, hands-on labs and real-world scenarios will help you apply these concepts. By the course's end, you'll be designing and implementing advanced generative AI applications with Amazon Bedrock. Please note: The hands-on exercises are optional and require access to your own AWS account. Completing these activities may result in minimal usage charges.

Syllabus

Module 1: Knowledge Bases and Workflows

In this module, you will explore how to improve generative AI responses using Amazon Bedrock Knowledge Bases with retrieval-augmented generation (RAG). You will learn to parse and chunk content, integrate document storage, and use APIs to query structured knowledge. The module also introduces prompt management and prompt flows, enabling you to design dynamic AI workflows. Through labs and demos, you will build applications that ask questions, process responses, and chain prompts in real-world use cases.

Module 2: AI-driven Agents for Task Automation

This module dives into Amazon Bedrock Agents and how they automate tasks using agent instructions, actions, tools, and session memory. You will learn to create conversational flows, use inline and collaborative agents, and extend capabilities with Lambda functions. The module also covers the Converse API for building interactive applications with tool use and dynamic context management. Hands-on labs guide you through building agent-powered apps, such as booking systems and workflow automation solutions.