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AutoGen Training

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Master AutoGen, a powerful framework for building intelligent AI agents and multi-agent systems. This course equips you with the skills to create AI-driven workflows, automate complex tasks, integrate large language models (LLMs), and develop scalable AI applications through hands-on projects and real-world use cases. Gain practical expertise and earn an industry-recognized certification to accelerate your career in AI and automation.

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The AutoGen Training is designed for professionals and aspiring AI developers who want to build intelligent, autonomous, and collaborative AI applications using the AutoGen framework. This comprehensive program provides in-depth knowledge of creating AI agents, orchestrating multi-agent workflows, integrating Large Language Models (LLMs), and automating complex business processes.

Throughout the course, participants will gain hands-on experience in designing, developing, and deploying AI-powered solutions using AutoGen. The curriculum covers core concepts such as agent architecture, multi-agent communication, tool integration, workflow automation, prompt engineering, human-in-the-loop systems, debugging, and performance optimization. Learners will also explore real-world applications across customer support, software development, data analysis, research automation, and enterprise AI solutions.

With expert-led sessions, practical labs, and industry-relevant projects, this course enables learners to develop production-ready AI applications while following best practices for scalability, security, and responsible AI. Upon successful completion, participants will receive a certification that validates their expertise in AutoGen and AI agent development, preparing them for emerging roles in generative AI and intelligent automation.

  • Overview of AutoGen Framework
  • Understanding AI Agents and Multi-Agent Systems
  • AutoGen Architecture and Components
  • Installation and Environment Setup
  • AutoGen Ecosystem and Use Cases

  • Python Essentials for AI Development
  • Virtual Environments and Package Management
  • Working with APIs
  • JSON Handling and Data Processing
  • Error Handling and Debugging

  • Introduction to LLMs
  • Connecting AutoGen with OpenAI and Azure OpenAI
  • Model Configuration and Parameters
  • Prompt Engineering Best Practices
  • Token Management and Cost Optimization

  • Creating Assistant Agents
  • User Proxy Agents
  • Configuring Agent Behaviors
  • Memory and Context Management
  • Agent Lifecycle Management

  • Agent-to-Agent Communication
  • Group Chat and Collaborative Agents
  • Task Planning and Delegation
  • Human-in-the-Loop Workflows
  • Multi-Agent Decision Making

  • Function Calling
  • API Integration
  • Database Connectivity
  • External Tool Integration
  • Workflow Automation

  • Custom Agent Development
  • Agent Orchestration
  • Event-Driven AI Workflows
  • State Management
  • Performance Optimization

  • Logging and Debugging Techniques
  • Monitoring AI Agent Performance
  • Exception Handling
  • Security Best Practices
  • Responsible AI and Governance

  • AI-Powered Customer Support
  • Document Processing Automation
  • Research and Knowledge Assistants
  • Code Generation and Software Development
  • Business Process Automation

  • Design an End-to-End Multi-Agent AI Solution
  • Build an Intelligent Workflow Automation Application
  • Deploy and Test AI Agents
  • Performance Evaluation
  • Project Presentation and Best Practices
  • Understand the fundamentals of AutoGen and AI agent architectures.
  • Build, configure, and manage intelligent AI agents using the AutoGen framework.
  • Design and implement multi-agent systems for collaborative problem-solving.
  • Integrate Large Language Models (LLMs) with AutoGen applications.
  • Develop AI-powered workflows to automate complex business processes.
  • Implement prompt engineering techniques for improved agent performance.
  • Enable tool calling, API integration, and external system connectivity.
  • Build human-in-the-loop AI applications for enhanced decision-making.
  • Debug, monitor, and optimize AI agent performance.
  • Apply security, governance, and responsible AI best practices.
  • Develop end-to-end, production-ready AI agent solutions through hands-on projects.
  • Prepare for real-world enterprise applications using AutoGen and Generative AI technologies.

AutoGen is an open-source framework that enables developers to build intelligent AI agents and multi-agent systems using Large Language Models (LLMs). It simplifies the creation of AI applications capable of collaborating, reasoning, and automating complex tasks.

This course is ideal for AI/ML engineers, Python developers, software engineers, data scientists, automation professionals, solution architects, and anyone interested in building AI agent-based applications.

Participants should have a basic understanding of Python programming and familiarity with Generative AI or Large Language Models (LLMs). Knowledge of APIs and Git is beneficial but not mandatory.

Yes. Upon successfully completing the training, you will receive an industry-recognized AutoGen Training Online Certification from Multisoft AI, validating your skills in AI agent development and workflow automation.

The course includes hands-on labs and a capstone project where you'll build AI agents, develop multi-agent workflows, integrate external tools and APIs, and create real-world AI automation solutions using the AutoGen framework.

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This Course Includes:
  • Globally Recognized Certification
  • 24+ Hrs. of Expert-Led Training
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  • Practical, Hands-On Learning
  • Build Your Own AI-Powered App
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