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Course Outline
Introduction to Managed AI Agents
- Defining AgentCore
- Core features and service offerings
- Application scenarios across various sectors
Architecting Your Initial Agent
- Defining agent roles and objectives
- Setting up managed agent parameters
- Practical lab: developing a basic agent
Augmenting Agents with Memory and Tools
- Implementing 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 for application connectivity
- Practical lab: linking an agent to an application
Releasing Managed Agents
- Deployment strategies within AgentCore
- Scalability and operational best practices
- Practical lab: releasing a fully managed agent
Oversight and Observability
- Accessing metrics and dashboards in AgentCore
- Monitoring performance and utilisation
- Practical lab: creating a monitoring workflow
Best Practices and Emerging Trends
- Considerations for governance and compliance
- Enhancing usability and system reliability
- Future trajectories in managed AI agents
Recap and Recommended Next Steps
Requirements
- Foundational grasp of AI and machine learning principles
- Knowledge of cloud service environments
- Experience with application development processes
Target Audience
- AI enthusiasts
- Product managers
- Generalist developers
14 Hours