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Course Outline

Introduction to Managed AI Agents

  • Defining AgentCore
  • Primary features and service offerings
  • Industry-specific use cases

Designing Your First Agent

  • Defining agent roles and objectives
  • Setting up managed agent configurations
  • Practical lab: constructing a basic agent

Enhancing Agents with Memory and Tools

  • Incorporating persistence and contextual data
  • Connecting tools and APIs
  • Practical lab: expanding agent functionality

AgentCore Runtime and Gateway Fundamentals

  • Overview of runtime architecture
  • Gateway integration for application use
  • Practical lab: linking an agent to an application

Deploying Managed Agents

  • Deployment strategies within AgentCore
  • Considerations for scaling and operations
  • Practical lab: releasing a fully managed agent

Monitoring and Observability

  • AgentCore metrics and dashboard features
  • Monitoring performance and usage patterns
  • Practical lab: establishing a monitoring workflow

Best Practices and Emerging Trends

  • Governance and compliance factors
  • Strategies for improving usability and reliability
  • Future directions in managed AI agents

Wrap-up and Future Actions

Requirements

  • A foundational understanding of AI and machine learning principles
  • Awareness of cloud service ecosystems
  • Experience with application development processes

Target Audience

  • AI enthusiasts
  • Product managers
  • Generalist developers
 14 Hours

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