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Course Outline
Introduction to Managed AI Agents
- Overview of AgentCore
- Core features and available services
- 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 contextual memory
- Connecting external tools and APIs
- Practical lab: expanding agent capabilities
AgentCore Runtime and Gateway Basics
- Overview of runtime architecture
- Integrating the gateway with applications
- Practical lab: linking an agent to an application
Deploying Managed Agents
- Exploring deployment methods in AgentCore
- Addressing scaling and operational requirements
- Practical lab: deploying a fully managed agent
Monitoring and Observability
- Utilizing metrics and dashboards in AgentCore
- Tracking performance and usage patterns
- Practical lab: establishing a monitoring workflow
Best Practices and Future Trends
- Considerations for governance and compliance
- Optimizing for usability and system reliability
- Emerging trends in managed AI agents
Summary and Next Steps
Requirements
- Fundamental grasp of AI and machine learning principles
- Knowledge of cloud service ecosystems
- Basic familiarity with application development processes
Target Audience
- AI professionals and enthusiasts
- Product managers
- Generalist software developers
14 Hours