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Duration 14 hours
Course Outline
Fundamentals of Managed AI Agents
- Defining the role and scope of AgentCore
- Exploring primary features and service offerings
- Identifying industry-specific application scenarios
Architecting Your Initial Agent
- Defining agent objectives and functional roles
- Setting up managed agent parameters
- Practical session: constructing a basic agent structure
Augmenting Agent Intelligence with Memory and Tools
- Implementing data persistence and contextual awareness
- Connecting external tools and API endpoints
- Practical session: broadening agent operational capabilities
Understanding AgentCore Runtime and Gateway Mechanics
- Overview of the runtime architecture
- Integrating gateways for seamless application access
- Practical session: linking an agent to a live application
Rolling Out Managed Agents
- Evaluating deployment strategies within AgentCore
- Considering scalability and operational best practices
- Practical session: executing a complete managed agent deployment
Performance Monitoring and Insight Generation
- Leveraging metrics and visual dashboards in AgentCore
- Monitoring system health and usage patterns
- Practical session: establishing a comprehensive monitoring pipeline
Strategic Practices and Industry Trajectories
- Addressing governance and compliance standards
- Refining for enhanced user experience and system reliability
- Forecasting future advancements in managed AI agent technology
Key Takeaways and Future Pathways
Requirements
- A foundational grasp of artificial intelligence and machine learning principles
- General knowledge of cloud-based service ecosystems
- Previous exposure to standard application development cycles
Target Audience
- Professionals with a keen interest in AI technologies
- Product managers overseeing AI-driven solutions
- Developers with generalist technical skills
