Agentic AI : Building Multi Agent Systems and Intelligent Workflows

Hands-on modules on CrewAI , AutoGen , BabyAGI , multi agent systems, RAG, robotics, DevOps automation, security, UI, personal assistants, etc. Super broad excellent for diverse technical labs.

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Course Objectives
  • Teach the core architecture and design of agentic AI systems.
  • Explore advanced patterns including memory, planning, reflection, and multi agent collaboration.
  • Provide hands on practice with leading frameworks (LangGraph, crewAI , AutoGen , OpenAI Agents
  • Equip learners with deployment skills for production environments (APIs, containers, monitoring).
  • Build confidence in integrating governance, security, and ethical practices into technical builds.
Learning Outcomes

By the end of the course, participants will be able to:

  • Architect end to end agentic AI workflows with modular frameworks.
  • Implement memory, planning, and multi agent communication in real applications.
  • Deploy agents securely with APIs, Docker/Kubernetes, and monitoring tools.
  • Integrate RAG (Retrieval Augmented Generation) and external APIs into agents.
  • Deliver a functional prototype of a domain specific AI agent.
Who should attend?
  • Software engineers, data scientists, and solution architects
  • Technical product managers and AI engineers
  • Professionals working in AI, RPA, or workflow automation
  • Startup builders creating AI driven products and platforms
  • Anyone with coding proficiency (Python recommended) seeking to master agentic systems
Course Outline
  • Foundations of Agentic AI Systems
  • Agent Design Patterns
  • Building Multi Agent Workflows
  • Integration with RAG & APIs
  • Advanced Architecturesy
  • Deployment & Monitoring
  • Governance & Security
  • Capstone Project & Demo