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Course Outline

Introduction to Managed AI Agents

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

Designing Your First Agent

  • Conceptualizing 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 awareness
  • Connecting external tools and APIs
  • Practical lab: Expanding agent capabilities

AgentCore Runtime and Gateway Fundamentals

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

Deploying Managed Agents

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

Monitoring and Observability

  • Utilizing metrics and dashboards in AgentCore
  • Monitoring performance and usage patterns
  • Practical lab: Developing a monitoring workflow

Best Practices and Emerging Trends

  • Navigating governance and compliance requirements
  • Optimizing for usability and system reliability
  • Futuristic directions in managed AI agents

Conclusion and Path Forward

Requirements

  • Foundational knowledge of AI and machine learning principles
  • Working familiarity with cloud-based services
  • Previous exposure to application development cycles

Intended Audience

  • AI enthusiasts
  • Product managers
  • Generalist developers
 14 Hours

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