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Duration 14 hours
Course Outline
Foundations of Managed AI Agents
- An introduction to AgentCore
- Overview of key features and services
- Industry-specific use cases
Architecting Your Initial Agent
- Defining agent roles and strategic objectives
- Setting up managed agent configurations
- Practical lab: constructing a basic agent
Expanding Agent Capabilities via Memory and Tools
- Implementing persistence and contextual awareness
- Connecting external tools and APIs
- Practical lab: broadening agent functionality
Basics of AgentCore Runtime and Gateway
- Overview of the runtime architecture
- Gateway integration for application connectivity
- Practical lab: linking an agent to an application
Rolling Out Managed Agents
- Exploring deployment options within AgentCore
- Considerations for scaling and operations
- Practical lab: deploying a fully managed agent
Oversight and Visibility
- Utilizing metrics and dashboards in AgentCore
- Making use of performance and usage tracking
- Practical lab: establishing a monitoring workflow
Best Practices and Emerging Trends
- Addressing governance and compliance standards
- Enhancing usability and system reliability
- Future directions in managed AI agents
Wrap-up and Path Forward
Requirements
- Fundamental knowledge of AI and machine learning principles
- Working familiarity with cloud service platforms
- Exposure to standard application development lifecycles
Target Audience
- AI technology enthusiasts
- Product managers
- Generalist software developers
