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Course Outline

Fundamentals of Managed AI Agents

  • Defining AgentCore and its scope
  • Core features and service offerings
  • Industry-specific application scenarios

Architecting Your Initial Agent

  • Defining agent roles and objective outcomes
  • Setting up managed agent parameters
  • Practical session: Constructing a basic agent

Augmenting Agents via Memory and Tooling

  • Implementing persistence and contextual awareness
  • Incorporating external tools and APIs
  • Practical session: Extending agent capabilities

Core AgentCore Runtime and Gateway Concepts

  • Overview of runtime architecture
  • Gateway integration strategies for applications
  • Practical session: Linking an agent to an application

Deploying Managed Agents

  • Available deployment modalities within AgentCore
  • Scalability and operational best practices
  • Practical session: Releasing a fully managed agent

Monitoring and Observability Frameworks

  • Leveraging metrics and dashboards in AgentCore
  • Performance and usage tracking methodologies
  • Practical session: Establishing a monitoring workflow

Strategic Best Practices and Future Trajectories

  • Governance and compliance frameworks
  • Optimizing for user experience and system reliability
  • Emerging trends in managed AI agent technology

Conclusion and Path Forward

Requirements

  • Foundational knowledge of AI and machine learning principles
  • Working familiarity with cloud service architectures
  • Basic exposure to application development processes

Target Audience

  • AI professionals and enthusiasts
  • Product managers
  • Generalist developers
 14 Hours

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