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Course Outline

Introduction to Managed AI Agents

  • Overview of AgentCore
  • Core features and available services
  • Industry-specific use cases

Designing Your First Agent

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

Enhancing Agents with Memory and Tools

  • Implementing persistence and contextual memory
  • Connecting external tools and APIs
  • Practical lab: expanding agent capabilities

AgentCore Runtime and Gateway Basics

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

Deploying Managed Agents

  • Exploring deployment methods in AgentCore
  • Addressing scaling and operational requirements
  • Practical lab: deploying a fully managed agent

Monitoring and Observability

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

Best Practices and Future Trends

  • Considerations for governance and compliance
  • Optimizing for usability and system reliability
  • Emerging trends in managed AI agents

Summary and Next Steps

Requirements

  • Fundamental grasp of AI and machine learning principles
  • Knowledge of cloud service ecosystems
  • Basic familiarity with application development processes

Target Audience

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

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