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Course Outline

Introduction to Managed AI Agents

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

Designing Your Initial Agent

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

Augmenting Agents with Memory and Tools

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

AgentCore Runtime and Gateway Fundamentals

  • Overview of runtime architecture
  • Gateway integration for applications
  • Practical lab: linking an agent to an application

Deploying Managed Agents

  • Deployment strategies within AgentCore
  • Scaling and operational factors
  • Practical lab: launching a fully managed agent

Monitoring and Observability

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

Best Practices and Emerging Trends

  • Governance and compliance factors
  • Optimizing for usability and reliability
  • Future directions in managed AI agents

Summary and Next Steps

Requirements

  • Foundational knowledge of AI and machine learning principles
  • Acquaintance with cloud service ecosystems
  • Exposure to standard application development workflows

Target Audience

  • AI enthusiasts
  • Product managers
  • Generalist developers
 14 Hours

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