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Duration 14 hours
Course Outline
Introduction to Managed AI Agents
- Defining AgentCore and its purpose
- Core features and available services
- Real-world applications across various sectors
Designing Your First Agent
- Defining the roles and objectives of the agent
- Setting up configurations for managed agents
- Practical lab: constructing a basic agent
Enhancing Agents with Memory and Tools
- Incorporating persistence and contextual awareness
- Connecting external tools and APIs
- Practical lab: expanding agent capabilities
AgentCore Runtime and Gateway Basics
- Overview of the runtime architecture
- Integrating the gateway for application connectivity
- Practical lab: linking an agent to an application
Deploying Managed Agents
- Exploring deployment strategies within AgentCore
- Considerations for scaling and operations
- Practical lab: rolling out a fully managed agent
Monitoring and Observability
- Utilizing metrics and dashboards in AgentCore
- Monitoring performance and resource usage
- Practical lab: creating a monitoring workflow
Best Practices and Future Trends
- Addressing governance and compliance requirements
- Strategies for improving usability and reliability
- Looking ahead at emerging trends in managed AI agents
Wrap-up and Recommendations for Next Steps
Requirements
- A foundational understanding of artificial intelligence and machine learning principles
- Basic familiarity with cloud service ecosystems
- Experience with general application development processes
Target Audience
- Professionals interested in AI technologies
- Product managers
- Generalist software developers
