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Course Outline

Introduction to Managed AI Agents

  • Defining AgentCore
  • Core features and service offerings
  • Application scenarios across various sectors

Architecting Your Initial Agent

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

Augmenting Agents with Memory and Tools

  • Implementing 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 for application connectivity
  • Practical lab: linking an agent to an application

Releasing Managed Agents

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

Oversight and Observability

  • Accessing metrics and dashboards in AgentCore
  • Monitoring performance and utilisation
  • Practical lab: creating a monitoring workflow

Best Practices and Emerging Trends

  • Considerations for governance and compliance
  • Enhancing usability and system reliability
  • Future trajectories in managed AI agents

Recap and Recommended Next Steps

Requirements

  • Foundational grasp of AI and machine learning principles
  • Knowledge of cloud service environments
  • Experience with application development processes

Target Audience

  • AI enthusiasts
  • Product managers
  • Generalist developers
 14 Hours

Number of participants


Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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