Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Foundations of Multi-Agent Systems
- Defining multi-agent systems within the broader AI ecosystem
- Key advantages and associated challenges
- Relevant enterprise use cases and practical applications
Leveraging AgentCore for Multi-Agent Orchestration
- Overview of AgentCore’s orchestration architecture
- Coordinating multiple agents across diverse workflows
- Practical lab: Orchestrating basic agent interactions
Models for Collaboration and Communication
- Patterns for message passing and shared memory
- Strategies for negotiation and task distribution
- Practical lab: Building agent collaboration protocols
Agent Specialization and Role Definition
- Crafting specialized agents for distinct operational tasks
- Striking a balance between agent autonomy and system coordination
- Practical lab: Developing role-specific agents
Scaling Multi-Agent Environments
- Architectural requirements for enterprise-level scalability
- Techniques for performance monitoring and load balancing
- Practical lab: Expanding the scale of an orchestrated agent system
Governance, Security, and Regulatory Compliance
- Ensuring auditability and observability in multi-agent workflows
- Implementing permissioning and security frameworks
- Case study: Navigating compliance in regulated industries
Future Trajectories in Multi-Agent AI
- Evolving trends in autonomous collaboration
- New research directions in agent collectives
- Strategic considerations for enterprise adoption
Conclusion and Path Forward
Requirements
- Comprehensive understanding of AI and machine learning systems
- Practical experience in designing distributed systems
- Proficiency with AWS services and cloud-native architectures
Target Audience
- System architects
- AI researchers
- Enterprise strategy teams
