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Course Outline
Introduction to Managed AI Agents
- Understanding 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 awareness
- Connecting tools and APIs
- Practical lab: Expanding agent capabilities
Fundamentals of AgentCore Runtime and Gateway
- Overview of runtime architecture
- Integrating gateways for application connectivity
- Practical lab: Linking an agent to an application
Deploying Managed Agents
- Deployment strategies within AgentCore
- Scaling and operational best practices
- Practical lab: Deploying a fully managed agent
Monitoring and Observability
- Utilizing metrics and dashboards in AgentCore
- Tracking performance metrics and usage patterns
- Practical lab: Establishing a monitoring workflow
Best Practices and Future Trends
- Considerations for governance and compliance
- Strategies for optimizing usability and reliability
- Emerging developments in managed AI agents
Summary and Next Steps
Requirements
- Foundational knowledge of AI and machine learning principles
- Proficiency with cloud services
- Experience with application development processes
Target Audience
- AI enthusiasts
- Product managers
- Generalist developers
14 Hours