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Course Outline

Introduction to AgentCore and Agentic AI

  • Agentic AI in the enterprise context.
  • Core components of AgentCore.
  • Positioning within the AWS Bedrock ecosystem.

AgentCore Runtime and Gateway

  • Configuring the AgentCore Runtime.
  • Secure API integration via Gateway.
  • Practical exercise: deploying a sample agent.

Memory and Stateful Agents

  • Implementing persistent context.
  • Designing long-running agent workflows.
  • Practical exercise: enabling session-based memory.

Identity, Permissions, and Security

  • Role-based access management for AI agents.
  • Identity federation and enterprise integration.
  • Practical exercise: configuring agent permissions.

Observability and Monitoring

  • Logging and tracing functionalities with AgentCore.
  • Metrics for usage analysis and performance monitoring.
  • Practical exercise: implementing observability dashboards.

Scaling and Orchestrating Multi-Agent Systems

  • Design patterns for multi-agent collaboration.
  • Strategies for performance optimization and reliability.
  • Practical exercise: orchestrating specialized agents.

Governance and Compliance

  • Auditability and safe large-scale rollout.
  • Compliance frameworks supported by AWS.
  • Best practices for regulated industries.

Summary and Next Steps

Requirements

  • Familiarity with cloud-based AI/ML services.
  • Practical experience with AWS ecosystem tools.
  • Understanding of enterprise security and observability principles.

Target Audience

  • AI/ML engineers.
  • DevOps leads.
  • Solution architects.
 14 Hours

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