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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
- Conceptualizing agent roles and objectives
- Setting up managed agent configurations
- 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 Fundamentals
- Overview of runtime architecture
- Gateway integration for application connectivity
- Practical lab: Linking an agent to an application
Deploying Managed Agents
- Exploring deployment options within AgentCore
- Considerations for scaling and operations
- Practical lab: Releasing a fully managed agent
Monitoring and Observability
- Utilizing metrics and dashboards in AgentCore
- Monitoring performance and usage patterns
- Practical lab: Developing a monitoring workflow
Best Practices and Emerging Trends
- Navigating governance and compliance requirements
- Optimizing for usability and system reliability
- Futuristic directions in managed AI agents
Conclusion and Path Forward
Requirements
- Foundational knowledge of AI and machine learning principles
- Working familiarity with cloud-based services
- Previous exposure to application development cycles
Intended Audience
- AI enthusiasts
- Product managers
- Generalist developers
14 Hours