AI Automation Training with n8n

Most teams buy an automation tool and never get past the first workflow. This training teaches your ops and marketing teams to build, test, and govern workflows with n8n, adding AI steps where they help and keeping people in the loop where it matters. The program stays grounded in the workflows your team actually needs to fix.

modules
6
hours
13
Contact us

Why this training

Why master this AI skill?

Why did we buy n8n six months ago and still do half of this by hand? This training answers that directly. It teaches your ops and marketing teams to build, test, and govern n8n workflows, add an AI step wherever messy input breaks a rigid rule, and hand the result to someone who can maintain it after the trainer leaves.

Most teams already own an automation tool and still run everything by hand, because the blocker was never the license. It's knowing how to design, build, and trust a workflow end to end, especially once an AI step is doing some of the thinking. That's the skill this training builds, on your own processes instead of a generic demo.

Over two days you map which processes are worth automating, build and test workflows in n8n, add AI steps for classification and summarization, and connect the apps you already run through APIs and webhooks. Automation here means deterministic, trigger-based pipelines. A workflow that reasons toward a goal has crossed into agent territory. A different program covers that ground. The remaining tracks are indexed under AI training.

The glue work never ends

Copy-paste between apps, weekly reports, data entry, chasing approvals: every team loses hours to repetitive work that follows the same steps every time, which is exactly the work a workflow can carry.

The tools are already there

Plenty of teams already pay for n8n, Make, or Zapier and still run everything by hand. The license is rarely the blocker. Knowing how to design and trust a workflow end to end is.

Why does one bad email break a rigid workflow?

Classic automation breaks on messy input. One free-text email with the wrong format, and a rigid workflow stalls. An LLM step can classify the request, pull the fields out anyway, or summarize the document, so the pipeline handles cases a fixed rule never could.

Stop waiting on someone else to build it

When every small change means a ticket to IT or an agency, automation stalls before it starts. Teams that can build and adjust their own workflows move faster, and call in outside help only where it's genuinely needed.

One shared login is often the whole security model

A workflow that touches customer data, runs unmonitored, and lives in one person's personal login is a liability waiting for its first bad week. Doing this well means credentials, monitoring, and KVKK-aware choices from day one, including self-hosting when data can't leave your systems.

Syllabus

Training syllabus

  1. Automation thinking: spotting work worth automating

    90 minBeginner

    Before touching a tool, teams learn to see their own work as processes. They also learn which ones automation genuinely fits. This module builds the judgment that keeps you from automating the wrong thing well.

    • Mapping a process step by step, from trigger to outcome
    • Spotting the repetitive, rule-bound work automation fits
    • Effort-versus-payoff triage: what to automate first
    • What an AI step adds beyond classic if-this-then-that
    • Where automation ends

  2. Workflow fundamentals with n8n

    150 minBeginner

    The core building blocks of a no-code workflow, learned by building one. Participants leave able to read, run, and fix a workflow in n8n, the primary tool for the hands-on sessions.

    • What n8n is, and how it compares to Make and Zapier
    • Triggers and nodes for your first connected workflow
    • Credentials and account connections, stored and handled safely
    • Testing a workflow and reading its execution log
    • Errors and retries, handled so a workflow doesn't fail silently
    • Cloud versus self-hosted n8n: what changes for your data

  3. Adding AI steps to your workflows

    150 minIntermediate

    Where automation stops being rigid. Participants add language-model steps to a workflow and learn to get structured, checkable output instead of a wall of prose. That's the difference between a demo and a pipeline you can actually rely on.

    • Calling an LLM as a step inside a workflow
    • Classification, summarization, extraction, and routing tasks
    • Prompt patterns that return structured, machine-readable output
    • AI output, checked first
    • Controlling cost and quality on high-volume runs
    • When a plain rule is more reliable than a model

  4. Connecting your apps and keeping humans in the loop

    120 minIntermediate

    Real workflows span systems: a form, a sheet, a CRM, an inbox. This module connects them cleanly and puts a person back in the loop wherever a mistake would be expensive.

    • Working with APIs and webhooks without writing much code
    • Spreadsheets, CRM, helpdesk, and email, integrated into one flow
    • Passing data cleanly between steps and systems
    • Human-in-the-loop checkpoints where a mistake would be costly
    • Approvals, notifications, fallbacks

  5. Automating a workflow from your own work

    150 minIntermediate

    At the heart of the program, each team picks one of its own processes and builds it end to end so participants leave with a working automation.

    • One of your team's own processes, chosen to automate live
    • Building it end to end, from trigger to result
    • Marketing-ops examples, from reporting to content ops to lead enrichment
    • Back-office examples, from intake to data entry to document handling
    • Testing with everyday cases and handing it to the team
    • A documented workflow that others can maintain

  6. Governance for trusted automation within data boundaries

    120 minAdvanced

    What separates a clever workflow from one an organization can still run five years from now. Security, data handling, monitoring, and the habits that keep automation from sprawling out of anyone's control.

    • Credentials, access, and security, managed across every workflow
    • Keeping data KVKK-compliant, including when to self-host
    • Monitoring running automations and catching failures early
    • Workflows that get versioned and maintained as they grow
    • No shadow-automation sprawl
    • Measuring hours saved and planning what to automate next

Outcomes

Outcomes & audience

What you will learn

  • A working n8n workflow you built and tested. You can debug it yourself
  • Judge fast whether a process is worth automating
  • Add an LLM step for classification, extraction, summarization, or routing, with output someone checks
  • Connect apps through APIs and webhooks, or use a shared sheet
  • A human catches costly mistakes
  • Tell workflows from agents
  • Keep workflow data KVKK-compliant, self-hosting n8n where needed
  • Monitor automations and measure the hours they save

Who should attend

  • Operations and business-operations managers
  • Marketing-ops and revenue-ops teams
  • Finance and HR, including back-office teams with repetitive workflows
  • Citizen developers and internal automation champions
  • Team leads who bought an automation tool and want it finally adopted
  • Analysts and coordinators who live in spreadsheets and manual handoffs

Format

Training format

Automation work fills two days, usually split into half-day sessions. Onsite and live-online formats cover the same syllabus, and every participant builds workflows in a live n8n instance.

Format
Onsite or live online
Duration
2 days (about 13 hours, can be split into half-day sessions)
Group size
Up to 16 participants per group
Language
English or Turkish
Materials
n8n workflow templates, a prompt library, and an exercise workbook
Certificate
Certificate of completion

About Zeo

Why Zeo

Zeo started in 2011 and now works out of San Francisco, Istanbul, Ankara, and Lisbon. We run Copilot Academy and organize Digitalzone, an international digital marketing conference. This program draws on the 10+ years of consulting and training work behind that, applied to corporate AI adoption.

  • 2011founded in Istanbul
  • 10+years of consulting and training experience
  • 3offices: San Francisco, Istanbul, Ankara, Lisbon

Keep exploring

Make & Zapier6 modules · 13 hoursTraining to build, test, and govern AI-enabled automations in Make and Zapier: connectors, AI steps, data mapping, and no-code governance that doesn't fall apart in month three.View trainingAI Agents6 modules · 13 hoursNo-code AI agents training for business and operations teams: what an agent really is, when to use one, and how to build and govern one on your own workflows, from Copilot Studio to custom GPTs.View trainingOpenClaw6 modules · 12 hoursInstructor-led OpenClaw training for business teams piloting a fast-moving, self-hosted personal AI assistant: a contained setup, scoped business workflows, review discipline before anything ships, and a governed call on whether to roll it out.View trainingUsing AI in Business Operations6 modules · 12 hoursAI training for business operations and shared-services teams, built around the SOPs, exception queues, and status reports that already fill their week, with sign-off and escalation staying exactly where they are today.View training

Next step

Let's find the first workflow to automate

What does your team repeat every week, and which tools do you already use? We'll pick the workflow and tools first. The session depth follows from that.
Contact us
Illustrated figure practicing at a desk in front of a large screen of prompt windows

Questions

Frequently asked questions