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Course Outline
Introduction to Managed AI Agents
- An overview of AgentCore
- Highlighting core features and available services
- Exploring real-world applications across various sectors
Designing Your First Agent
- Defining the role and objectives of your agent
- Setting up managed agent parameters
- Practical exercise: constructing a basic agent
Expanding Agent Capabilities with Memory and Tools
- Incorporating data persistence and contextual awareness
- Connecting external tools and APIs
- Practical exercise: broadening the agent’s functional scope
Foundations of AgentCore Runtime and Gateway
- Review of the runtime architecture
- Integrating the gateway for application compatibility
- Practical exercise: linking an agent to a specific application
Deploying Managed Agents
- Exploring deployment strategies within AgentCore
- Addressing scalability and operational best practices
- Practical exercise: releasing a fully managed agent
Monitoring and Observability
- Utilizing metrics and dashboards provided by AgentCore
- Monitoring performance indicators and usage patterns
- Practical exercise: establishing a monitoring workflow
Best Practices and Future Directions
- Considering governance and compliance standards
- Focusing on usability and system reliability
- Identifying emerging trends in managed AI agents
Conclusion and Recommended Next Steps
Requirements
- A solid grasp of fundamental AI and machine learning principles
- Working knowledge of cloud-based services
- Experience with standard application development processes
Target Audience
- Technology professionals interested in AI
- Product managers
- Developers with a generalist skillset
14 Hours
