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Duration 14 hours
Course Outline
AgentCore and Agentic AI Fundamentals
- The role of Agentic AI in enterprise environments
- Key architectural components of AgentCore
- Contextualising AgentCore within the broader AWS Bedrock ecosystem
AgentCore Runtime and Gateway
- Configuring the AgentCore Runtime environment
- Achieving secure API integration through Gateway
- Practical task: deploying a sample agent
Memory and Stateful Agents
- Creating persistent context mechanisms
- Structuring long-duration agent workflows
- Practical task: activating session-based memory
Identity, Permissions, and Security
- Applying role-based access controls to AI agents
- Managing identity federation and enterprise-level integrations
- Practical task: setting up agent permission structures
Observability and Monitoring
- Utilising logging and tracing features in AgentCore
- Tracking usage metrics and performance indicators
- Practical task: constructing observability dashboards
Scaling and Orchestrating Multi-Agent Systems
- Architectural patterns for multi-agent collaboration
- Strategies for performance optimisation and system reliability
- Practical task: orchestrating specialised agents
Governance and Compliance
- Ensuring auditability and safe, scalable rollouts
- Overview of compliance frameworks supported by AWS
- Best practices for sectors with regulatory requirements
Recap and Recommended Next Steps
Requirements
- A foundational understanding of cloud-based AI and ML services
- Familiarity with the AWS ecosystem and its tooling
- Awareness of enterprise security and observability principles
Target Audience
- AI and ML engineers
- DevOps leaders
- Solution architects
