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 Duration 14 hours

Course Outline

Introduction to Managed AI Agents

  • Defining AgentCore
  • Core features and available services
  • Industry-specific applications

Architecting Your First Agent

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

Expanding Agents with Memory and Tools

  • Incorporating persistence and contextual awareness
  • Connecting external tools and APIs
  • Practical lab: broadening agent functionalities

Understanding AgentCore Runtime and Gateway

  • Overview of runtime architecture
  • Integrating gateways for application support
  • Practical lab: linking an agent to an application

Launching Managed Agents

  • Deployment methodologies in AgentCore
  • Considerations for scaling and operations
  • Practical lab: releasing a fully managed agent

Oversight and Observability

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

Best Practices and Emerging Trends

  • Addressing governance and compliance requirements
  • Enhancing usability and system reliability
  • Future advancements in managed AI agents

Conclusion and Subsequent Actions

Requirements

  • A foundational grasp of AI and machine learning principles
  • Knowledge of cloud service ecosystems
  • Experience with application development processes

Target Audience

  • Individuals interested in AI technologies
  • Product managers
  • Generalist developers

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