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Course Outline
Introduction to Managed AI Agents
- Defining AgentCore
- Essential features and services
- Industry-specific use cases
Designing Your First Agent
- Defining agent roles and objectives
- Setting up managed agent parameters
- Practical lab: constructing a basic agent
Expanding Agents with Memory and Tools
- Incorporating persistence and contextual awareness
- Integrating external tools and APIs
- Practical lab: enhancing agent capabilities
Foundations of AgentCore Runtime and Gateway
- Overview of runtime architecture
- Gateway integration for application connectivity
- Practical lab: linking an agent to an application
Rolling Out Managed Agents
- Deployment strategies within AgentCore
- Considerations for scaling and operations
- Practical lab: deploying a fully managed agent
Monitoring and Observability
- Utilizing metrics and dashboards in AgentCore
- Monitoring performance and usage patterns
- Practical lab: creating a monitoring workflow
Best Practices and Emerging Trends
- Governance and compliance factors
- Optimizing for usability and reliability
- Future directions in managed AI agents
Wrap-up and Path Forward
Requirements
- A foundational grasp of AI and machine learning principles
- Experience with cloud-based services
- Previous exposure to application development processes
Intended Audience
- Individuals interested in AI
- Product managers
- Generalist developers
14 Hours
