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Duration 14 hours
Course Outline
Introduction to AgentCore and Agentic AI
- The role of Agentic AI within enterprise environments
- Overview of the fundamental components of AgentCore
- The place of AgentCore within the AWS Bedrock ecosystem
AgentCore Runtime and Gateway
- Initialising and configuring the AgentCore Runtime
- Achieving secure API integration via Gateway
- Hands-on task: Deploying a prototype agent
Memory and Stateful Agents
- Creating and managing persistent context
- Structuring workflows for long-running agent operations
- Hands-on task: Activating session-based memory capabilities
Identity, Permissions, and Security
- Applying role-based access controls to AI agents
- Managing identity federation and integration with enterprise systems
- Hands-on task: Setting up specific agent permissions
Observability and Monitoring
- Utilising logging and tracing features in AgentCore
- Tracking usage metrics and performance indicators
- Hands-on task: Building custom observability dashboards
Scaling and Orchestrating Multi-Agent Systems
- Key design patterns for collaborative multi-agent systems
- Strategies for performance tuning and system reliability
- Hands-on task: Co-ordinating specialised agents for complex tasks
Governance and Compliance
- Ensuring audit trails and safe, large-scale rollouts
- Adhering to compliance frameworks supported by AWS
- Industry best practices for operating in regulated sectors
Wrap-up and Future Pathways
Requirements
- Foundational knowledge of cloud-based AI/ML services
- Proficiency with the AWS ecosystem and its core tools
- Familiarity with enterprise security standards and observability principles
Target Audience
- AI/ML Engineers
- DevOps Team Leads
- Solution Architects
