Amazon Bedrock AI Agents - Masterclass

Name: Amazon Bedrock AI Agents - Masterclass
Rating: 4.6 (372 reviews)

Build Intelligent AI Agents with Amazon Bedrock — Step-by-Step Guide to Tools, Lambdas, Function Calling, and Deployment

Created byPaulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor

Last updated 6/2025

English

English [Auto],Spanish [Auto],

What you'll learn

Hands-on walkthroughs using the AWS Bedrock Console and APIs
Integration with Knowledge Bases, tools, and external APIs
Deploy a full Agentic Workflow and expose to a Client App
Amazon Bedrock Agents best practices

Course content

6 sections • 23 lectures • 2h 1m total length

Introduction3:07
Explore the fundamentals of amazon bedrock agents, implement ai agents via the bedrock console and api, and learn workflow orchestration and best practices.
Course Structure1:19
Explore the course structure that pairs theory with hands-on practice, starting with fundamental concepts and then integrating practical work throughout to reinforce learning in the amazon bedrock ai agents masterclass.
AWS Account Knowledge - Pre-reqs0:55

Amazon Bedrock Deep Dive - What is It and Benefits4:29
Explore Amazon Bedrock as a fully managed, serverless service with a single API, offering diverse foundation models and private, enterprise-ready customization to build secure AI agents.
Amazon Bedrock Key Features and Security Privacy and Safety5:51
Explore how Amazon Bedrock enables AI for enterprises with model customization and retrieval augmented generation, while ensuring data privacy, encryption, and governance through CloudWatch, CloudTrail, and S3.
Amazon Bedrock Pricing3:47
Explore Amazon Bedrock pricing and the economics of using foundation models via on-demand, batch, or provisioned throughput plans, with model inferencing, customization, and marketplace options.
Pricing IMPORTANT NOTE --- PLEASE READ --0:28
Hands-on: Amazon Bedrock Console Walkthrough - Playground10:19
Join a hands-on walkthrough of the Amazon Bedrock console, exploring foundation models, model catalogs, access requests, and an open playground for testing text, image, and multimodal models across providers.
Hands-on - Generate Images3:28
Explore the image and video playground in Amazon Bedrock, request access to Stable Diffusion models, and generate icons and images while noting pay-by-inference pricing.

Amazon Bedrock Agent Deep Dive - Basic Workflow6:27
Explore how Amazon Bedrock agents orchestrate tasks using foundation models, prompts, and tools, and how observer and executor agents, memory context, and knowledge bases enable planning and transparent execution.
Detailed Flow of Bedrock Agent - Full Overview4:28
Understand how Amazon Bedrock Agent orchestrates tasks by combining conversation history, context, knowledge bases, and tools, using chain-of-thought planning and action groups to call APIs.
Hands-on: Build our First Amazon Bedrock Agent - Simple Agent10:00
Build a simple Amazon bedrock agent from scratch in the console, choosing a foundation model and configuring instructions with a knowledge base for retrieval augmented generation.
Hands-on: Adding Knowledge Base and Testing It13:17
Build and test a knowledge base for an Amazon Bedrock AI agent by creating an S3-backed vector store, uploading AWS PDFs, and validating retrieval.
Hands-on: Action Groups - Adding a Lambda Function12:26
Create and configure action groups in Amazon Bedrock AI Agents by adding lambda functions, defining function details or API schemas, and wiring tools to fetch time and other data.
Amazon Bedrock Agent and Action Groups - Architectural Overview2:22
Map the AWS Bedrock agent architecture with action groups and JSON or YAML OpenAI API schema. Trace how Lambda processes requests via API gateway to external systems and returns results.
Amazon Bedrock Agent Architectural Overview and Animation5:09
Explore the AWS Bedrock agents architecture, with a central Bedrock agent sustained by a foundation model, an orchestration layer, knowledge bases, pluggable actions, and AWS Lambda integrations.
Build-time vs Runtime Operations - Overview2:22
Explain build-time versus runtime operations in Amazon Bedrock AI agents, detailing agent preparation and versioning, deployment, invoke API, and orchestration with pre-processing, post-processing, and external data fetch via Lambda.
Amazon Bedrock Agents - Creation Process & Benefits4:38
Discover how to create Amazon Bedrock agents, configure foundation models, roles, and prompts, connect Lambda functions and knowledge bases, and deploy with versions and aliases for secure integration with AWS.

Hands-on: Scraper Agent - Console Setup13:56
Build and deploy a scraper agent in Amazon Bedrock with console setup, configuring a Lambda-based web scraper that fetches and cleans page content using BeautifulSoup and API schema.
Hands-on: Create an Agent Alias - Agent Deployment2:18
Deploy the scraper agent by saving, creating an alias, attaching a version, and testing the alias to verify accurate web scraping results.
Final - Scraper Agent Frontend Client8:39
Build a Python Streamlit frontend to connect to an AWS Bedrock agent using env variables and SigV4 authentication, then crawl web content and extract main points with conversation history.

Requirements

AWS Services Fundamentals
Have an AWS Account
Programming Fundamentals

Description

Unlock the full potential of Amazon Bedrock Agents and learn how to build scalable, intelligent AI-powered applications—from concept to production.

This course is a hands-on, practical guide for developers, architects, and technical product managers looking to integrate advanced orchestration capabilities into their applications using Amazon Bedrock's Agent framework.

What You’ll Learn:

What Amazon Bedrock Agents are and why they’re changing how we build intelligent applications.
How to set up Bedrock Agents using both the AWS Console and the full API.
How to decompose user queries into steps, use Knowledge Bases (KBs), invoke actions, and manage dynamic flows using Agents.
Full walkthrough of the Bedrock Agent API—including invoking Agents from client applications like Streamlit.
Deep dive into multi-agent orchestration, advanced use cases, and best practices.
Final capstone project: Build and deploy a production-ready enterprise chatbot that integrates documents, databases, and APIs.
Advanced integration with Lambda, guardrails, traces, and action groups.
Gain the skills to automate business workflows, build internal tools, and power customer-facing apps with dynamic, AI-driven capabilities.

Tools & Technologies Covered:

Amazon Bedrock (Agents, KBs, API)
AWS Lambda, SAM, and Serverless deployment
Streamlit for frontend integration
API-first development with Bedrock Agents
Enterprise-level orchestration patterns

This Course Includes:

Hands-on walkthroughs using the AWS Bedrock Console and APIs
Real code examples from AWS Labs and AWS serverless blogs
Integration with Knowledge Bases, tools, and external APIs
Complete source code and templates to build your own AI workflows

Who this course is for:

Developers and software engineers looking to integrate LLM-based agents into real apps
Solution architects building AI orchestration systems on AWS
Anyone curious about building intelligent tools using generative AI, function calling, and multi-agent systems

Amazon Bedrock AI Agents - Masterclass

What you'll learn

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Course content

Introduction3 lectures • 5min

Source Code and Resources1 lecture • 1min

Amazon Bedrock Deep Dive6 lectures • 28min

Amazon Bedrock AI Agents - Deep Dive9 lectures • 1hr 1min

Capstone Project - Web Scraper Agent - Full Workflow3 lectures • 25min

Wrapup1 lecture • 2min

Requirements

Description

Who this course is for: