Building Multi-Agentic Workflows on AWS Bedrock + AgentCore

About this course

Want to build AI applications where multiple agents collaborate, remember users, and run in production? This course takes you from multi-agent fundamentals to deploying intelligent, memory-enabled agents on AWS Bedrock and AgentCore.

You'll build a fully operational travel planner where Supervisor Agents coordinate tasks while Collaborator and Helper Agents handle database lookups, API calls, and travel preferences on your behalf. You'll also build a personal assistant agent with live web search powered by DuckDuckGo — capable of fetching real-time information and responding with up-to-date answers.

What You'll Learn:

Multi-Agent Design — When to break tasks into specialized agents, how to handle inter-agent communication, and how to ensure seamless collaborationAWS Bedrock LLMs — Customize prompt templates, override parameters, and optimize AI output using foundation models

Serverless Deployment — Store data in S3, build with Lambda Action Groups, and deploy via API Gateway for live, scalable requests

AgentCore Runtime — What Amazon Bedrock AgentCore is and how to deploy and run agents at scale on purpose-built infrastructure

Web Search Agents — Build agents using the Strands framework with Claude Haiku that search the web in real time via DuckDuckGoShort-Term Memory — Track conversation context within a session using AgentCore's get_last_k_turnsLong-Term Memory — Configure extraction strategies that automatically capture Semantic facts, User Preferences, and Session Summaries — so your agents remember users across sessions

Understanding the AWS agent harness and runtime architecture

Read the full description on Udemy on Udemy (opens in a new tab)

Prices, discounts and availability are set by Udemy. We may earn a commission when you purchase through links on this site.