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Course Outline

Overview of Managed AI Agents

  • Defining AgentCore
  • Essential features and services
  • Cross-industry use cases

Architecting Your Initial Agent

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

Augmenting Agents with Memory and Tools

  • Incorporating persistence and context
  • Connecting tools and APIs
  • Practical lab: expanding agent capabilities

Foundations of AgentCore Runtime and Gateway

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

Deploying Managed Agents

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

Supervision and Observability

  • Metrics and dashboards in AgentCore
  • Monitoring performance and utilization
  • Practical lab: creating a monitoring workflow

Best Practices and Emerging Trends

  • Focus on governance and compliance
  • Optimizing for usability and reliability
  • Future trajectories in managed AI agents

Recap and Subsequent Steps

Requirements

  • Foundational knowledge of AI and machine learning principles
  • Acquaintance with cloud services
  • Experience with application development workflows

Target Audience

  • AI enthusiasts
  • Product managers
  • Generalist developers
 14 Hours

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