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Course Outline

Introduction to Managed AI Agents

  • Defining AgentCore
  • Core features and service offerings
  • 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 context
  • Connecting tools and APIs
  • Practical lab: expanding agent features

AgentCore Runtime and Gateway Fundamentals

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

Deploying Managed Agents

  • Deployment strategies within AgentCore
  • Scalability and operational factors
  • Practical lab: releasing a fully managed agent

Monitoring and Observability

  • Metrics and dashboard utilization in AgentCore
  • Tracking performance and resource usage
  • Practical lab: establishing a monitoring workflow

Best Practices and Future Trends

  • Compliance and governance strategies
  • Optimizing for reliability and user experience
  • Emerging trends in managed AI agents

Summary and Next Steps

Requirements

  • A foundational knowledge of AI and machine learning principles
  • Experience with cloud-based services
  • Exposure to application development processes

Target Audience

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

Number of participants


Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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