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Multi-Agent Programming with n8n Course

Class Dates
(click date for class times)
(click Enroll for locations)
8/4-8/5
Class Dates and Times
08/04/2026Tuesday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
08/05/2026Wednesday10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
Last Reg Date7/30
 
9/1-9/2
Class Dates and Times
09/01/2026Tuesday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
09/02/2026Wednesday10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
 
9/30-10/1
Class Dates and Times
09/30/2026Wednesday10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
10/01/2026Thursday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
 
10/27-10/28
Class Dates and Times
10/27/2026Tuesday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
10/28/2026Wednesday10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
 
11/24-11/25
Class Dates and Times
11/24/2026Tuesday 10:00-4:45 EST
  9:00-3:45 CST
  8:00-2:45 MST
  7:00-1:45 PST
11/25/2026Wednesday10:00-4:45 EST
  9:00-3:45 CST
  8:00-2:45 MST
  7:00-1:45 PST
 
Fee:  $995

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Multi-Agent Programming with n8n Course

 

Overview

Multi-agent programming is reshaping how organizations automate complex work by coordinating teams of specialized AI agents that can plan, reason, use tools, and hand off tasks to one another. This course provides a hands-on introduction to designing and deploying multi-agent systems using n8n, the popular open-source workflow automation platform and its built-in, LangChain-powered AI Agent nodes. Participants will learn how to build agents that connect to language models, memory, tools, and data sources, then orchestrate several agents together to automate real-world business processes.

Designed for developers, automation specialists, and AI professionals, this course equips learners to build reliable multi-agent workflows on a single n8n canvas: scoping each agent to a clear responsibility, wiring up an orchestrator that delegates to specialist agents, validating and structuring agent outputs, and exposing or consuming tools through the Model Context Protocol (MCP). By the end, participants will understand how to apply multi-agent automation to practical use cases—research, content production, data processing, and customer-facing workflows—while addressing key reliability, ethical, and security considerations.

Note: As n8n and the broader agentic AI ecosystem evolve, the course content will be updated periodically to reflect new nodes, features, and best practices.

Prerequisites

Basic knowledge of Generative AI and large language models is required. Familiarity with APIs and basic automation concepts is recommended, but not required.

COURSE OUTLINE

Introduction to AI Agents and Multi-Agent Systems

  • Understanding agentic automation and its role in modern workflows
  • How AI agents differ from traditional, linear automations
  • Real-world examples of multi-agent systems in business workflows

Getting Started with n8n for Agentic Workflows

  • Orientation to the n8n canvas: nodes, triggers, and executions
  • How n8n builds AI on LangChain with root and sub-nodes
  • Connecting your first language model and credentials

Building Your First AI Agent with the AI Agent Node

  • Anatomy of the AI Agent node: chat model, prompt, and tools
  • Triggering agents with the Chat Trigger and workflow triggers
  • Adding memory for multi-turn context and conversation history

Giving Agents Tools and Structured Outputs

  • Connecting tools: HTTP Request, Code, Calculator, and integrations
  • Writing clear tool descriptions so agents choose the right tool
  • Enforcing reliable outputs with the Structured Output Parser

Grounding Agents with RAG and Vector Stores

  • Why retrieval matters: reducing hallucinations with private data
  • Building an ingestion pipeline: loaders, splitters, and embeddings
  • Using vector stores as a retriever tool for AI agents

Designing Multi-Agent Systems in n8n

  • The orchestrator pattern: a manager agent that delegates work
  • Using the AI Agent Tool node to call agents as tools
  • Worked example: orchestrating a research agent and a writer agent

Connecting Agents with the Model Context Protocol (MCP)

  • What MCP is and how it standardizes tool discovery and calls
  • Exposing n8n workflows as tools with the MCP Server Trigger
  • Consuming external tools with the MCP Client Tool node

Reliability, Reusability, and Scaling

  • Wrapping repeatable steps in reusable sub-workflows
  • Sequential vs. parallel execution across multiple agents
  • Error handling, retries, and verification checks for dependable runs

Deployment, Monitoring, and Responsible AI

  • Deploying workflows on n8n Cloud or self-hosted environments
  • Monitoring latency, errors, and cost while auditing agent decisions
  • Bias, accountability, data privacy, and security best practices

 

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LDLAPR

Attend hands-on, instructor-led Multi-Agent Programming with n8n training classes at ONLC's nationwide locations. Not near one of our locations? Attend these same live classes from your home/office PC via our Remote Classroom Instruction (RCI) technology.

For additional training options, check out our list of Courses and select the one that's right for you.

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