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Course Outline

Introduction to Managed AI Agents

  • Defining AgentCore
  • Core features and available services
  • Industry-specific use cases

Creating Your First Agent

  • Defining agent roles and objectives
  • Setting up managed agent parameters
  • Practical lab: Constructing a basic agent

Expanding Agent Capabilities with Memory and Tools

  • Incorporating persistence and contextual awareness
  • Connecting external tools and APIs
  • Practical lab: Broadening agent functionality

Foundations of AgentCore Runtime and Gateway

  • Overview of runtime architecture
  • Gateway integration for application connectivity
  • Practical lab: Linking an agent to an application

Releasing Managed Agents

  • Deployment strategies within AgentCore
  • Scalability and operational factors
  • Practical lab: Launching a fully managed agent

Observability and Monitoring

  • Utilizing metrics and dashboards in AgentCore
  • Monitoring performance and consumption
  • Practical lab: Creating a monitoring pipeline

Best Practices and Future Directions

  • Governance and regulatory compliance
  • Enhancing usability and system reliability
  • Trends in the evolution of managed AI agents

Conclusion and Next Steps

Requirements

  • Foundational knowledge of AI and machine learning principles
  • Awareness of cloud computing services
  • Exposure to standard application development processes

Target Participants

  • AI professionals
  • Product managers
  • Generalist developers
 14 Hours

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