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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