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Duration 14 hours
Course Outline
Overview of Managed AI Agents
- Introduction to AgentCore
- Primary features and service offerings
- Industry-specific applications
Creating Your Initial Agent
- Defining agent roles and objectives
- Setting up managed agent parameters
- Practical lab: constructing a basic agent
Expanding Agent Capabilities with Memory and Tools
- Incorporating persistence and contextual awareness
- Connecting external tools and APIs
- Practical lab: augmenting agent functionality
Foundations of AgentCore Runtime and Gateway
- Review of runtime architecture
- Integrating the Gateway with applications
- Practical lab: linking an agent to an application
Launching Managed Agents
- Deployment strategies within AgentCore
- Considerations for scaling and operations
- Practical lab: releasing a fully managed agent
Observation and Monitoring
- AgentCore metrics and dashboard tools
- Monitoring performance and usage patterns
- Practical lab: establishing a monitoring pipeline
Industry Standards and Emerging Trends
- Compliance and governance factors
- Improving usability and system reliability
- Future developments in managed AI agents
Conclusion and Path Forward
Requirements
- Foundational knowledge of AI and machine learning principles
- Acquaintance with cloud-based services
- Experience with application development processes
Intended Participants
- AI professionals and enthusiasts
- Product managers
- Generalist developers
