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Course Outline

Introduction to Managed AI Agents

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

Designing Your First Agent

  • Defining agent roles and objectives
  • Setting up managed agent parameters
  • 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
  • Integrating the gateway into applications
  • Practical lab: Linking an agent to an application

Deploying Managed Agents

  • Exploring deployment options within AgentCore
  • Addressing scaling and operational needs
  • Practical lab: Launching a fully managed agent

Monitoring and Observability

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

Best Practices and Emerging Trends

  • Considering governance and compliance frameworks
  • Optimizing for user experience and reliability
  • Future directions in managed AI agents

Summary and Next Steps

Requirements

  • A foundational understanding of AI and machine learning principles
  • Proficiency with cloud service environments
  • Experience with application development workflows

Target Audience

  • AI enthusiasts
  • Product managers
  • Generalist developers
 14 Hours

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