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Course Outline
Introduction to Managed AI Agents
- Defining AgentCore
- Core features and available 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
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
- Integrating the gateway into applications
- Practical lab: Linking an agent to an application
Deploying Managed Agents
- Exploring deployment options within AgentCore
- Addressing scaling and operational needs
- Practical lab: Launching 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
- Considering governance and compliance frameworks
- Optimizing for user experience and reliability
- Future directions in managed AI agents
Summary and Next Steps
Requirements
- A foundational understanding of AI and machine learning principles
- Proficiency with cloud service environments
- Experience with application development workflows
Target Audience
- AI enthusiasts
- Product managers
- Generalist developers
14 Hours