AI Training · Make & Zapier
AI Automation Training with Make & Zapier
Most teams that adopt Make or Zapier build one connected workflow, then stop there. This hands-on training teaches yours to design, build, test, and govern full scenarios and zaps — adding AI steps where messy input needs judgment, and keeping a person in the loop wherever a mistake would be costly.
The program runs inside whichever platform your team already chose, so people leave with automations built on their own stack. Exercises use your team's real connectors and forms wherever possible, including the approval steps.
- modules
- 6
- hours
- 13
Some of the 500+ brands we've worked with
Selected brands we’ve worked with across industries.
MeteksanGlobalCase Study
VisperaGlobalCase Study
Why this training
Why train on this tool?
Most teams think buying Make or Zapier is the automation project. It's the starting gun. The actual project is designing a scenario or zap that keeps working once messy business data hits it, and knowing when an AI step earns its place instead of just looking clever.
Across the program, participants compare Make's branching canvas against Zapier's linear builder, connect apps through native integrations and fallback webhooks, and add AI steps for classification and first-draft text with output they can check — the detailed module rebuilds one of your team's own scenarios end to end so the group leaves with a working automation. Governance runs alongside the build: naming who owns each connection, what data may enter a hosted tool, and how to keep a growing scenario library from sliding into unmanaged sprawl; teams weighing a broader, tool-neutral strategy or already on n8n should start with our AI automation training instead. Nothing here ships as a fixed script — connectors, approval steps, and compliance rules adjust to what your team already runs, as they do across the rest of our AI training programs.
The seat that only moves one spreadsheet
Many teams already pay for Make or Zapier and use it to connect one form to one spreadsheet — the subscription was never the blocker; designing, testing, and handing off a multi-step scenario is.
What happens when a zap meets messy input?
Classic triggers and filters need clean, predictable input — a native AI step reads a messy email, classifies a ticket, or drafts a first-pass reply so the automation keeps working.
No-code still needs governance
Because Make and Zapier remove the coding barrier, teams add automations faster than anyone tracks them — a scenario touching customer data or living in one person's login is a liability however easy it was to build.
Make and Zapier are not interchangeable
Make's visual, branching canvas favors complex data shaping, while Zapier's linear zaps favor speed and simplicity — pick the wrong one and you end up fighting the tool instead of the process.
Sprawl happens fast on a shared account
A handful of builders in the same workspace can produce dozens of overlapping scenarios within months — naming conventions, folders, and ownership need deciding early, or nobody can tell what still matters.
Syllabus
Training syllabus
Where Make and Zapier are each the stronger choice
90 minBeginner
Before building anything, teams learn the shared trigger-and-action model behind both platforms. They compare where each one wins the job. That judgment keeps the rest of the program grounded in the work at hand.
- Scenarios and zaps, and where each one fits
- The shared trigger-and-action model behind both
- Picking a first automation from your own repetitive work
- Where a no-code platform tops out
- Reading the release notes before you commit
Building your first scenario or zap
150 minBeginner
The core mechanics of a no-code automation, learned by building one in whichever platform your team runs. Participants leave able to connect apps and branch logic, then read a run's history without guessing.
- Connecting apps: OAuth and API keys, with account permissions
- Make's canvas versus Zapier's linear builder
- Filters and routers, with paths for branching logic
- Reading a run's history instead of guessing
- Handling errors and retries, including silent failures
Adding AI steps inside Make and Zapier
150 minIntermediate
Where a fixed scenario stops being fixed. Participants add a native AI step and learn to get structured, checkable output instead of a wall of prose, which is the difference between a demo and an automation you can trust.
- Native AI modules inside Make and Zapier
- Using an AI step for classification or first-draft text
- Prompting inside a no-code step for consistent output
- Passing AI output cleanly to the next step
- Guardrails against a silently corrupted downstream field
Data mapping and connecting your stack
120 minIntermediate
Because scenarios span a form, a sheet, a CRM, and a helpdesk, this module maps data between them cleanly and adds a fallback for apps without a native connector.
- Mapping fields across CRM, sheets, forms, and helpdesk
- Make's data structures versus Zapier's field-by-field mapping
- Webhooks and API calls when no connector exists
- Cleaning messy data mid-run
- A human approval step before live records change
Rebuilding one of your own scenarios end to end
150 minIntermediate
The center of the program. Each team picks one of its own scenarios or zaps and rebuilds it end to end, so participants leave with a working automation.
- Picking one of your team's own scenarios to rebuild
- End to end, in the platform you use
- Marketing and ops examples: lead routing and reporting, including content handoffs
- Back-office examples: intake forms and approvals, including document workflows
- Testing with live cases
- A build-doc a non-builder can follow
Governance of no-code automations
120 minAdvanced
What separates a clever automation from one an organization can run for years. Access control and monitoring sit beside the habits that keep a shared Make or Zapier workspace from sliding into unmanaged sprawl.
- Connections and credentials, with permissions in one place
- What should never enter a hosted no-code tool
- Catching silent failures early
- Version history and change control as automations multiply
- Shadow-automation sprawl on a shared account
- What graduates to n8n or custom code
Outcomes
Outcomes & audience
What you will learn
- Choose the platform on purpose
- Build one scenario, start to finish
- Add an AI step with output you can check
- Map data cleanly, with a fallback when a connector is missing
- Put a human in the loop before it touches live data
- Know what never belongs here
- Catch a silent failure before it costs a week
- The line between Make, Zapier, and custom code
Who should attend
- Marketing-ops and revenue-ops teams already living in Make or Zapier
- Operations and back-office staff still running approvals by hand
- Agencies maintaining automations for client accounts
- Growing SMB teams standardized on one platform
- Citizen developers and internal automation champions
- Whoever bought the Make or Zapier plan and wants it actually used
Format
Training format
This runs two days, usually split into half-day working sessions. Onsite and live online cover the same syllabus, and every participant builds scenarios or zaps in a live Make or Zapier workspace.
- 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
- Make and Zapier build templates, a prompt library, and an exercise workbook
- Certificate
- Certificate of completion
Keep exploring
Related programs
Next step
Put your Make or Zapier seat to work
Questions
Frequently asked questions
Which teams get the most out of this Make and Zapier course?
Any team already running, or wanting to run, repetitive work through a no-code platform: marketing-ops, revenue-ops, operations, finance, HR, agencies managing client accounts, and the internal champions building for their colleagues. No engineering background is assumed.
Is coding knowledge a prerequisite?
Both platforms are built for visual, no-code automation, and so is this course, so anyone who can read a spreadsheet formula already has enough to follow every exercise.
Why teach both platforms instead of picking one?
Most teams have already picked one of the two, and the underlying skill, trigger-and-action design, data mapping, AI steps, governance, transfers between them either way. We teach inside whichever platform your team runs, and the module on choosing between them helps teams still deciding.
How is this different from your broader AI Automation course?
Our AI Automation program is platform-neutral and built around n8n, which teams with strict data-residency needs can self-host. This one is deliberately specific to Make and Zapier, the tools most non-technical teams already have a paid seat for, and goes deeper on the connectors, pricing tiers, and governance features unique to each.
How many hours, and over what period?
However your calendar needs it: the full two days back to back, or split into half-day blocks so day-to-day work isn't disrupted. Instruction runs about 13 hours total and works onsite or live online. Every session uses a live Make or Zapier workspace.
Can you build around scenarios or zaps we already have?
That's the whole point of the rebuild module. We take a short brief in advance, collect a couple of your actual scenarios or zaps, and build the exercises around the systems you already connect: CRM, sheets, helpdesk, and the rest.
What does it come to?
It depends on group size, delivery format, customization depth, and location, roughly in that order of weight. Tell us the platform and the team, and the figure we send back reflects your setup.
What about our data during the sessions?
Session data is synthetic or anonymized by default, and nothing live goes into a shared workspace on day one. One module covers handling live client data compliantly, once a team is ready for that step. KVKK and data-residency rules get mapped to what a hosted no-code tool may actually hold. Where a process needs to stay on infrastructure you control, that becomes a self-hosted setup. We flag it early.