Generative AI

HRDC Reg. No: 10001553990
Duration: 3 Days (21 Hours)

Course Overview

This 3-day intensive program empowers AI developers and engineers to build intelligent, collaborative multi-agent systems using Microsoft AutoGen. Participants will learn to implement advanced agent communication strategies, design human-in-the-loop workflows, integrate APIs and external tools, and orchestrate domain-specialized AI agents. The course focuses on hands-on practice and real-world use cases to help you confidently create, manage, and deploy AI-powered automation systems using cutting-edge open-source frameworks.

Who Should Attend

• AI and ML Engineers

• Python Developers

• Technical Architects

• Automation Engineers

• R&D and Innovation Teams

Why Choose This Course

This HRDC claimable course (Reg. No: 10001553990) is designed to help technical professionals master AutoGen, Microsoft's open-source framework for creating LLM-powered multi-agent systems. With a deep dive into advanced tools like Swarm, Magentic One, and GraphFlow, participants will build the skills needed to lead intelligent automation projects across industries.

Learning Outcomes

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

• Design and implement AutoGen-based multi-agent systems

• Leverage tools and APIs for enhanced agent capability

• Implement complex interaction patterns: RoundRobin, Selector, Swarm, etc.

• Create human-in-the-loop and autonomous workflows

• Use structured responses and model contexts for precision tasks

• Customize agents for specific domain functions and control logic

• Develop scalable AI systems with persistence, state management, and agent orchestration

Prerequisites

• Intermediate Python programming skills

• Basic understanding of LLMs and their role in AI systems

Teaching Methodology

• Interactive instructor-led sessions

• Live demonstrations and technical walkthroughs

• Hands-on coding labs using AutoGen

• Case-based discussions and architecture reviews

• Group Q&A and troubleshooting sessions

• Final real-world mini project