Mastering Amazon Bedrock AgentCore: Bring your PoC to Prod!

Learn how to build AI Agents on AWS and how to follow best practices to make your AI Agents ready for production.

What you’ll learn
Understand the requirements in production for agentic AI workloads
Learn the fundamental components of Amazon Bedrock AgentCore
Deploy AI Agents for scale, performance, security and reliability
Hands-On Development of Agentic solution with Strands SDK, MCP, Rest APIs, OAuth and Memory

Requirements
Python
GenAI Basics
AWS Basics

Description
This course contains the use of artificial intelligence.Master Amazon Bedrock AgentCore and build production-ready AI agents in just 4 hours. This comprehensive course takes you from zero to deploying intelligent, multi-agent systems that integrate with real enterprise tools—all using AWS’s newest agentic AI platform.Whether you’re an enterprise developer rushing to deploy AI agents in production, or a seasoned AWS engineer transitioning into agentic AI, this course gives you everything you need to build sophisticated AI systems that actually ship to production.What You’ll Learn – Foundation & Core Services:AgentCore Quick Start – Deploy your first intelligent agent in 15 minutes using Amazon BedrockAgentCore Runtime Integration – Master ANY agent framework: Strands, LangGraph, CrewAI, or custom Python implementationsAgentCore Gateway – Connect agents to MCP servers, third-party APIs, and internal tools with secure credential managementAgentCore Memory – Implement conversation history, long-term memory, and context-aware agents that remember user preferencesAgentCore Identity – Handle OAuth flows, API key management, and IAM integration for secure, multi-user agent systemsAgentCore Observability – Leverage the Amazon CloudWatch GenAI Observability Dashboard and integrate with 3rd Party tools via OpenTelemetryAgentCore Code Interpreter – Let agents write and execute Python code dynamically for data analysis and computationAgentCore Browser Tools – Enable agents to navigate websites, extract data, and interact with web applications autonomouslyHands-On Learning: 8+ Production LabsThis isn’t just lectures—you’ll build real applications through comprehensive, step-by-step labs:Lab 0: Setup your AWS Account, Amazon Kiro and use the AWS Free TierLab 1: AgentCore Runtime – Deploy your first Bedrock AgentCore Runtime agent with Strands SDK and Claude Sonnet, test locally, and understand the core architecture. Lab 2: Gateway – Connect your agent to real-world Weather, Flight and Exchange rate API sources using MCP and AgentCore Gateway with API Key authentication.Lab 3: Memory – Build a customer service agent with conversation history, user profile memory, and context-aware responses across sessions.Lab 4: Identity & OAuth – Implement secure 3LO OAuth agents with Google OAuth to create documents in your Google Drive, credential management, and per-user data isolation.Lab 5: Code Interpreter Tools – Create a data analysis agent that writes Python code, generates visualizations, and performs statistical analysis on user data.Lab 6: Browser Tools – Build a research agent that navigates websites, extracts information, and compiles reports automatically.Lab 7: Integrate everything into one Agent – Create one AgentCore Runtime Agent that connects to Gateway with all MCP Tools for weather, flight and exchange rate.

Who this course is for
Cloud Architects
AI Beginners
Software Developers
Product Managers
Software Architects
Cloud Engineers

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