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Course Outline
Introduction to Managed AI Agents
- Overview of AgentCore
- Essential features and service offerings
- Real-world applications across various sectors
Creating Your First Agent
- Defining agent objectives and roles
- Setting up managed agent configurations
- Practical lab: constructing a basic agent
Expanding Agent Capabilities with Memory and Tools
- Implementing state retention and context awareness
- Connecting external tools and APIs
- Practical lab: enhancing agent functionality
Foundations of AgentCore Runtime and Gateway
- High-level view of the runtime architecture
- Integrating the gateway with application layers
- Practical lab: linking an agent to a user application
Release of Managed Agents
- Available deployment strategies within AgentCore
- Considerations for scaling and operations
- Practical lab: releasing a fully managed agent
Observability and Performance Monitoring
- Utilizing metrics and dashboards in AgentCore
- Monitoring usage patterns and system performance
- Practical lab: creating a monitoring pipeline
Best Practices and Emerging Trends
- Addressing governance and regulatory compliance
- Improving reliability and user experience
- Future outlook for managed AI agents
Wrap-up and Recommended Path Forward
Requirements
- A foundational grasp of artificial intelligence and machine learning principles
- General knowledge of cloud service ecosystems
- Experience with standard application development processes
Target Audience
- Individuals with a keen interest in AI
- Product management professionals
- Generalist software developers
14 Hours