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Building Agentic AI with Amazon Bedrock AgentCore

SS Course: 73904

Course Overview

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In this course, youll explore the core principles and strategies for designing Agentic AI systems using AWS services. Youll learn how Agentic AI differs from traditional conversational systems, and how to use tools like Strands Agents SDK, and Amazon Bedrock AgentCore to build autonomous, goal-driven solutions that solve real-world problems.                                                                  

Scheduled Classes

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04/24/26 - TDV - Virtual-Instructor Led - Virtual-Instructor Led (click to enroll)

What You'll Learn

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Define agentic AI characteristics and differentiate them from traditional AI systems.
  • Ensure compliance with data governance and audit requirements.
  • Implement different tool integration patterns, including built-in tools and protocol-based tools.
  • Design and deploy Model Context Protocol (MCP) servers and clients for extensible agent capabilities.
  • Describe common authentication patterns for agent tool use.
  • Configure AgentCore Gateway components for secure and authorized tool access.
  • Implement agentic memory patterns for different use cases.
  • Configure AgentCore Memory operations for context-aware development.
  • Optimize memory performance for production workloads.
  • Configure AgentCore Observability for production monitoring.
  • Implement Amazon CloudWatch integration and specialized tracing.
  • Identify the core agent components and their interactions.
  • Describe the core features of AgentCore Evaluations.
  • Integrate agentic systems with production APIs and services.
  • Design deployment strategies for production environments.
  • Assess production readiness and establish continuous improvement processes
  • Describe how Bedrock AgentCore services support agentic AI.
  • Deploy agents by using supported frameworks with AgentCore Runtime.
  • Describe the core features of AgentCore Runtime.
  • Configure serverless execution with session isolation.
  • Configure AgentCore Identity for enterprise security requirements.
  • Create policies to secure agent tool calls using AgentCore Policy.
  • Implement secure token management and permission delegation.
  • In this course learners will:

Outline

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Agent building blocks
  • Amazon Bedrock AgentCore introduction
  • Supported frameworks and implementation
  • AgentCore Runtime overview
  • Infrastructure and deployment
  • Security and identity management
  • Securing your agents with AgentCore Identity
  • Amazon Bedrock AgentCore Policy
  • Built-in tools and custom integration
  • Model Context Protocol (MCP)
  • AgentCore Gateway
  • Implementing AgentCore Gateway
  • Amazon Bedrock AgentCore Policy
  • Agentic memory core concepts
  • AgentCore Memory
  • Securing AgentCore Memory
  • Monitoring agents with AgentCore Observability
  • Verifying agent performance with AgentCore Evaluation
  • Next steps and additional resources
  • Course summary

Prerequisites

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Agentic AI Foundations
  • We recommend that attendees of this course have:

    Who Should Attend

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      Next Step Courses

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