Generative AI Applications with Amazon Bedrock

Name: Generative AI Applications with Amazon Bedrock
Rating: 1.0 (1 reviews)

Agent Orchestration

Created byAmazon Web Services (AWS)

Last updated 11/2025

English

What you'll learn

Understand retrieval-augmented generation (RAG) concepts.
Create and query Amazon Bedrock knowledge bases.
Design workflows using prompts and flows.
Configure Bedrock agents with custom tasks.

Course content

6 sections • 22 lectures • 2h 21m total length

Introduction to the Course3:15
Explore building production-ready generative ai apps with Amazon Bedrock, using private knowledge bases, retrieval augmented generation, prompt management, flows, and agents to orchestrate multi-step tasks.
Course Roadmap

Introduction to Amazon Bedrock Knowledge Bases4:39
Explore turning internal runbooks into a queryable knowledge base with Amazon Bedrock knowledge bases, using retrieval augmented generation, embeddings, and vector search to answer DevOps questions with sources.
Demonstration of Amazon Bedrock Knowledge Bases8:15
Demonstrates building a Bedrock knowledge base from S3 data, generating embeddings, and querying with the retrieve and generate API to retrieve relevant runbooks.
Amazon Bedrock Knowledge Bases2:58

Introduction to Amazon Bedrock Prompt Management6:44
Explore Bedrock prompt management to create, version, and reuse prompts with templates and variables; configure variants and ARNs, and use with InvokeModel or Converse to handle dynamic transcripts.
Prompt Management1:35
Exercise: Prompt Management with Amazon Bedrock12:48
Converse API and Tool Use Part 111:15
Learn to build conversational apps on Amazon Bedrock using the Converse API to maintain context across turns by passing historical messages and system prompts, with prompt templates.
Converse API and Tool Use Part 27:14
Learn to use the Converse API and tools to enable a model to invoke code and external systems, such as an AWS Lambda weather tool, to fetch current weather.
Exercise: Working with the Amazon Bedrock API9:19
Converse APIs3:46
Introduction to Amazon Bedrock Flows8:02
Drag and drop Bedrock flow nodes to build generative AI workflows, connecting inputs and outputs with flow logic, using prompt nodes and AWS service integrations.
Amazon Bedrock Flows1:51
Module 1 Quiz

Amazon Bedrock Agents6:02
Discover how Amazon Bedrock agents orchestrate foundation models, data sources, apps, and user conversations to complete tasks, using action groups, memory, and retrieval-augmented generation with knowledge bases.
Demonstration of Amazon Bedrock Agents7:11
Demonstrates using a prebuilt bedrock agent with an agent builder, memory, guardrails, and action groups to query budget and expenditure by country via functions and orchestration, with tracing.
Amazon Bedrock Agents3:32
Exercise: Creating an HR Assistant Agent using Amazon Bedrock Agents15:51

Amazon Q Developer Security Scanning5:57
Explore how Amazon Q Developer scans your codebase for security vulnerabilities, hard-coded credentials, secrets, and misconfigurations with updated detectors that enforce AWS best practices.
Demo Amazon Q Developer Transform Agent3:00
Demonstrates using the Amazon Q Developer transform agent in Visual Studio Code to upgrade a Java 11 to 17 project, updating pom.xml, compiler settings, dependencies, and a Spring Boot upgrade.
Module 2 Quiz
Tech Talk: Using Agents, Knowledge Bases, and Converse API18:05
Learn how Bedrock agents orchestrate knowledge bases and tools via the Converse API to handle ambiguity, manage sessions with memory, and enable retrieval augmented generation with MCP-enabled tools.

Requirements

AWS experience

Description

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.

Who this course is for:

Participants should be comfortable with basic AI implementation in AWS and have hands-on experience with foundation models.

Generative AI Applications with Amazon Bedrock

What you'll learn

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Course content

Introduction to the Course2 lectures • 3min

Amazon Bedrock Knowledge Bases3 lectures • 16min

Amazon Bedrock Prompt Management and Flows9 lectures • 1hr 3min

AI-driven Agents for Task Automation4 lectures • 33min

Amazon Q Developer3 lectures • 27min

Course Wrap up1 lecture0

Requirements

Description

Who this course is for: