.png){kind=logo}
Multi-Agent Systems is a practical course designed to help learners understand, design, develop, orchestrate, evaluate, and deploy AI systems in which multiple specialized agents collaborate to complete complex tasks.
The course begins with multi-agent AI fundamentals and progresses into multi-agent architecture, agent roles, communication, coordination, shared state, task delegation, routing, and workflow design. Learners explore how multiple autonomous AI agents can work together through structured orchestration patterns instead of relying on a single agent for every task.
Learners also work with multi-agent frameworks and implementation approaches while understanding how to select appropriate architectures for different business and technical requirements. The curriculum covers sequential, parallel, conditional, hierarchical, supervisor, and handoff-based workflows.
Advanced topics include multi-agent RAG, knowledge retrieval, agent memory, context management, tool integration, multi-agent collaboration, evaluation, observability, security, governance, reliability, scalability, and production optimization.
Through practical projects, learners build multi-agent applications that combine specialized agents, orchestration, tools, knowledge retrieval, shared context, monitoring, and production-oriented practices.
.png&w=256&q=75){kind=small}
View on Google Maps