Course Description:
This course delves into the principles and applications of swarm intelligence and advanced multi-agent coordination. Learners will explore distributed decision-making, emergent behaviors, and enterprise-grade platforms for orchestrating complex AI systems at scale.
Lecture 1: Swarm AI Concepts
Learn the foundations of swarm AI, from multi-agent conversation passing to managing emergent behaviors in collective intelligence systems.
Key Objectives:
- OpenAI Swarm: Multi-agent conversation passing
- Collective intelligence principles
- Emergent behavior management
Lecture 2: Advanced Agent Coordination
Master coordination strategies for large-scale agent systems, including consensus mechanisms, conflict resolution, and distributed decision-making.
Key Objectives:
- Distributed decision making
- Consensus mechanisms
- Conflict resolution strategies
Lecture 3: Enterprise Platforms
Explore enterprise-ready platforms for multi-agent orchestration, data integration, and LLM operations. Learn how to combine human oversight with advanced AI workflows.
Key Objectives:
- Stack AI: Complex enterprise data integration
- AI Workforce: Human-in-the-loop systems
- Unify: Multi-model management and LLMOps
