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Course Outline
Foundations of Managed AI Agents
- Defining the role and purpose of AgentCore
- Overview of essential features and core services
- Industry-specific applications and scenarios
Architecting Your Initial Agent
- Defining agent objectives and functional roles
- Setting up configurations for managed agents
- Practical exercise: constructing a basic agent
Expanding Agent Capabilities with Memory and Tools
- Implementing data persistence and contextual awareness
- Connecting external tools and API interfaces
- Practical exercise: enhancing agent functionality
Core AgentCore Runtime and Gateway Concepts
- Understanding the underlying runtime architecture
- Integrating gateways for application connectivity
- Practical exercise: linking an agent to a specific application
Launching Managed Agents into Production
- Exploring deployment pathways within AgentCore
- Addressing scalability and operational efficiency
- Practical exercise: executing a fully managed deployment
Performance Monitoring and System Observability
- Utilizing AgentCore metrics and visual dashboards
- Maintaining oversight of performance and resource usage
- Practical exercise: establishing a robust monitoring workflow
Strategic Best Practices and Emerging Trends
- Navigating governance and compliance requirements
- Refining agents for optimal usability and dependability
- Exploring future advancements in managed AI agent technology
Conclusion and Recommended Progression
Requirements
- A foundational grasp of AI and machine learning principles
- General knowledge of cloud service ecosystems
- Basic experience with software development lifecycles
Intended Learners
- Professionals interested in AI technologies
- Product managers involved in AI initiatives
- Developers with generalist technical skills
14 Hours