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Course Outline

Introduction to Managed AI Agents

  • Defining AgentCore
  • Essential features and service components
  • Industry-specific use cases

Architecting Your Initial Agent

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

Augmenting Agents with Memory and Tools

  • Implementing persistence and contextual awareness
  • Connecting external tools and APIs
  • Practical lab: Expanding agent functionality

AgentCore Runtime and Gateway Fundamentals

  • Overview of runtime architecture
  • Integrating the Gateway with applications
  • Practical lab: Linking an agent to an application

Deploying Managed Agents

  • Exploring deployment strategies within AgentCore
  • Considerations for scaling and operations
  • Practical lab: Launching a fully managed agent

Monitoring and Observability

  • Utilizing AgentCore metrics and dashboards
  • Monitoring performance and utilization
  • Practical lab: Creating a monitoring workflow

Best Practices and Emerging Trends

  • Governance and compliance frameworks
  • Enhancing usability and system reliability
  • Future directions in managed AI agents

Conclusion and Future Directions

Requirements

  • A foundational grasp of AI and machine learning principles
  • Working knowledge of cloud-based services
  • Previous exposure to application development processes

Target Audience

  • Enthusiasts of artificial intelligence
  • Product managers
  • Generalist developers
 14 Hours

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