Who it's for
For people who finished the n8n beginner course or already run workflows, and can read a little JavaScript. Lessons 1 to 3 work on n8n Cloud and self-hosted, and lesson 4 needs a server of your own with Docker.
Lessons
- 1n8n error workflow: the Error Trigger, retries and Stop And ErrorBuild an n8n error workflow with the Error Trigger, read the data it receives, then set retries, On Error and Stop And Error on the nodes that fail.
- 2n8n sub-workflow: the Execute Sub-workflow node and its triggerBuild an n8n sub-workflow with the Execute Sub-workflow Trigger, pass data in and out, convert existing nodes and learn when to split a workflow.
- 3n8n Code node: JavaScript, Python, item modes and common errorsLearn the n8n Code node: Run Once for All Items against Each Item, $input and the return shape, native Python, item linking, limits and common errors.
- 4n8n queue mode: Redis, workers, concurrency and scalingRun n8n in queue mode: how main, Redis and workers fit together, the Postgres setup, worker concurrency, binary data rules and webhook processors.
Frequently asked questions
Who is the n8n advanced course for?
It is for people who already build workflows in n8n and want to run them in production. Finish the beginner course first, because these lessons skip the canvas, the first trigger and the first webhook.
Do the lessons work on n8n Cloud?
Lessons 1 to 3 do, on Cloud and self-hosted alike, with one difference: Cloud allows only the crypto and moment modules in the Code node. Lesson 4 covers queue mode, a self-hosted setup you run with Postgres, Redis and Docker.
Which version of n8n do the lessons follow?
The documentation as it stood on 5 November 2026, including n8n 3.0, in early access since 27 October 2026 with a stable release due in early December. That release removes the Function and Function Item nodes, cuts the task runner timeout to 60 seconds and ends in-memory binary data. Each lesson says where a change touches it.
Is this n8n course free?
Yes, every lesson is free to read. You can follow lessons 1 to 3 on the free self-hosted Community edition, though the docs mark a few features, such as log streaming and multi-main, as Enterprise.
What should I learn after this course?
The Dify course is next: it builds AI apps, a knowledge base and agents in Dify. Before that, pick a finished workflow from Mindket's n8n directory, add an error workflow to it and import it into the queue-mode setup from lesson 4.