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Course Outline

Overview of Managed AI Agents

  • Defining AgentCore
  • Core features and service offerings
  • Cross-industry application examples

Building Your Initial Agent

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

Expanding Agent Capabilities via Memory and Tools

  • Incorporating persistence and context
  • Connecting external tools and APIs
  • Practical lab: enhancing agent functionality

Foundations of AgentCore Runtime and Gateway

  • High-level view of runtime architecture
  • Gateway integration for software applications
  • Practical lab: linking an agent to an application

Rolling Out Managed Agents

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

Oversight and Observability

  • Utilizing metrics and dashboards in AgentCore
  • Monitoring performance and resource usage
  • Practical lab: establishing a monitoring pipeline

Optimal Practices and Future Directions

  • Governance and compliance frameworks
  • Improving usability and system reliability
  • Trends in the evolution of managed AI agents

Conclusion and Roadmap

Requirements

  • Fundamental knowledge of AI and machine learning principles
  • Working familiarity with cloud-based services
  • Experience with application development processes

Target Audience

  • AI enthusiasts
  • Product managers
  • Generalist developers
 14 Hours

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