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
Fundamentals of Multi-Agent Systems
- Defining multi-agent systems within the broader AI ecosystem
- Key advantages and inherent challenges
- Relevant enterprise use cases and applications
Leveraging AgentCore for Orchestration
- Understanding the AgentCore orchestration architecture
- Coordinating multiple agents across diverse workflows
- Practical lab: Orchestrating basic agent interactions
Models for Collaboration and Communication
- Message passing and shared memory design patterns
- Strategies for negotiation and task allocation
- Practical lab: Implementing agent collaboration protocols
Agent Specialization and Role Definition
- Architecting specialized agents for specific tasks
- Striking the right balance between autonomy and coordination
- Practical lab: Developing role-specific agents
Scaling Multi-Agent Architectures
- Architectural considerations for enterprise-level scale
- Techniques for performance monitoring and load balancing
- Practical lab: Scaling an orchestrated agent system
Governance, Security, and Compliance
- Ensuring auditability and observability in multi-agent workflows
- Implementing permissioning and security frameworks
- Case study: Navigating compliance in regulated sectors
Future Trajectories in Multi-Agent AI
- Evolving trends in autonomous collaboration
- Emerging research areas in agent collectives
- Strategic impact on enterprise adoption
Wrap-up and Future Pathways
Requirements
- A robust command 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
