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Course Outline

Introduction to Managed AI Agents

  • Overview of AgentCore
  • Essential features and service offerings
  • Real-world applications across various sectors

Creating Your First Agent

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

Expanding Agent Capabilities with Memory and Tools

  • Implementing state retention and context awareness
  • Connecting external tools and APIs
  • Practical lab: enhancing agent functionality

Foundations of AgentCore Runtime and Gateway

  • High-level view of the runtime architecture
  • Integrating the gateway with application layers
  • Practical lab: linking an agent to a user application

Release of Managed Agents

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

Observability and Performance Monitoring

  • Utilizing metrics and dashboards in AgentCore
  • Monitoring usage patterns and system performance
  • Practical lab: creating a monitoring pipeline

Best Practices and Emerging Trends

  • Addressing governance and regulatory compliance
  • Improving reliability and user experience
  • Future outlook for managed AI agents

Wrap-up and Recommended Path Forward

Requirements

  • A foundational grasp of artificial intelligence and machine learning principles
  • General knowledge of cloud service ecosystems
  • Experience with standard application development processes

Target Audience

  • Individuals with a keen interest in AI
  • Product management professionals
  • Generalist software developers
 14 Hours

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