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Course Outline

Foundations of Managed AI Agents

  • Defining the role and purpose of AgentCore
  • Overview of essential features and core services
  • Industry-specific applications and scenarios

Architecting Your Initial Agent

  • Defining agent objectives and functional roles
  • Setting up configurations for managed agents
  • Practical exercise: constructing a basic agent

Expanding Agent Capabilities with Memory and Tools

  • Implementing data persistence and contextual awareness
  • Connecting external tools and API interfaces
  • Practical exercise: enhancing agent functionality

Core AgentCore Runtime and Gateway Concepts

  • Understanding the underlying runtime architecture
  • Integrating gateways for application connectivity
  • Practical exercise: linking an agent to a specific application

Launching Managed Agents into Production

  • Exploring deployment pathways within AgentCore
  • Addressing scalability and operational efficiency
  • Practical exercise: executing a fully managed deployment

Performance Monitoring and System Observability

  • Utilizing AgentCore metrics and visual dashboards
  • Maintaining oversight of performance and resource usage
  • Practical exercise: establishing a robust monitoring workflow

Strategic Best Practices and Emerging Trends

  • Navigating governance and compliance requirements
  • Refining agents for optimal usability and dependability
  • Exploring future advancements in managed AI agent technology

Conclusion and Recommended Progression

Requirements

  • A foundational grasp of AI and machine learning principles
  • General knowledge of cloud service ecosystems
  • Basic experience with software development lifecycles

Intended Learners

  • Professionals interested in AI technologies
  • Product managers involved in AI initiatives
  • Developers with generalist technical skills
 14 Hours

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