
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.
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.
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.
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.
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 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.
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