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Home > Technical Courses > Artificial Intelligence > Multi-Agent Programming with n8n
Understand how to leverage agentic AI for business efficiency, software development, and intelligent decision-making—while addressing key ethical and security considerations.
Agentic Programming is transforming AI development by enabling autonomous, adaptable AI agents that can collaborate, plan, and execute tasks independently. This course provides a hands-on introduction to building and deploying intelligent AI agents using cutting-edge frameworks like Microsoft AutoGen, Magentic-One, and n8n. Participants will learn how to integrate AI agents into workflows, automate complex processes, and enhance productivity in real-world applications. Designed for developers, automation specialists, and AI professionals, this course equips learners with the skills to create multi-agent systems, validate AI-generated data, and implement best practices for AI-driven automation. By the end, participants will understand how to leverage agentic AI for business efficiency, software development, and intelligent decision-making—while also addressing key ethical and security considerations. Note: As AI technology evolves, the course content will be updated periodically to reflect new trends and advancements.
Category
ID
Duration
Level
Price
Artificial Intelligence
13921
2 Day(s)
Foundation
$995.00
Objectives
In this course, you will learn how to: • Use AI Agents and Agentic AI • Use Core Principles of Agent-Oriented Programming (AOP) • Build Intelligent AI Agents with AutoGen • Implement Multi-Agent Systems with Magentic-One • Validate and Structure Agentic Data with Pydantic • Use AI Agents in Business and Automation • Use GitHub and Copilot for AI-Assisted Development • Navigate Ethical Considerations and Challenges
Introduction to AI Agents and Agentic AI • Understanding agentic programming and its role in AI development • How AI agents differ from traditional software applications • Real-world examples of agentic AI in automation and business workflows Core Principles of Agent-Oriented Programming (AOP) • Key characteristics of AI agents: autonomy, adaptability, and interactivity • Multi-agent collaboration: How AI agents communicate and interact • Overview of agentic design patterns: reflection, tool use, planning, and multi-agent collaboration Building Intelligent AI Agents with AutoGen • Introduction to Microsoft’s AutoGen framework: Capabilities and use cases • Understanding the agent communication model and message passing • Designing and deploying agents using Python and AutoGen APIs • Using AutoGen Studio for rapid prototyping and workflow design Implementing Multi-Agent Systems with Magentic-One • What is Magentic-One? How it extends AutoGen for complex workflow • Orchestration of AI agents: Coordinating multiple specialized agents • Practical use cases: Task delegation, multi-step planning, and execution • Integrating AI Agents into Workflows with n8n • Introduction to n8n as a workflow automation tool • Connecting agents to external services: Email, Google Docs, and APIs • Automating repetitive tasks with AI-powered decision-making Validating and Structuring Agentic Data with Pydantic • Introduction to data validation in AI workflows • Using Pydantic to define schemas for AI-generated content • Ensuring structured and reliable outputs from AI agents AI Agents in Business and Automation • Automating email processing: Categorizing and summarizing incoming emails • AI-assisted content creation: Refining blog posts and generating business documents • Improving productivity with AI-driven workflow automation GitHub and Copilot for AI-Assisted Development • Understanding AI-powered code generation with GitHub Copilot • Best practices for integrating Copilot into Python and AutoGen development • Using Git for version control in agentic programming projects • GitHub and Copilot for AI-Assisted Development Ethical Considerations and Challenges • Understanding AI bias and accountability in autonomous agents • Security concerns and responsible AI usage in workflow automation • Best practices for monitoring and auditing AI agent decisions
Questions?
Basic knowledge of Generative AI is required. Understanding of Python programming concepts is recommended, but not required.
Multi-Agent Programming with n8n
Class Schedule
Live Online
Course Overview
Training Delivery Methods
With Productivity Point, you will have a spectrum of delivery methods to choose from... when where and how you like it. Whether it's in a classroom or online, we have a delivery option to meets your needs.
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