Training course · Make · Education & Teaching

Make for Educators

Automation with Make (formerly Integromat) and AI modules: build scenarios, routers and AI steps while keeping data protection in check.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Make for Educators” is designed for roles such as Teachers in general and vocational schools, University lecturers and Trainers in adult and continuing education and shows step by step how to use Make productively, safely and transparently in Education & Teaching – from the fundamentals to advanced workflows.

Make, formerly known as Integromat, is a visual automation platform that lets you connect applications and automate recurring processes without writing code. Over two days you will learn to build scenarios systematically, from triggers and modules through routers and filters to iterators, aggregators and data stores. You will understand how data flows through a scenario, how to reshape it with functions and how to keep an eye on operations consumption.

The second focus is AI. You connect language models through Make’s AI modules and provider integrations to classify text, extract information from emails and documents, draft replies or enrich content. You learn to catch errors with error handlers, test scenarios and document them clearly. Finally, you address data protection topics such as hosting region, data processing agreements and data minimisation, so that your automations can be run safely within your organisation.

Schools, universities, adult education providers and corporate academies are undergoing a fundamental shift with generative AI. Educators use AI assistants to differentiate teaching materials, create tasks at different levels, prepare feedback and write course descriptions. At the same time, AI challenges established assessment formats, coursework and the very notion of independent work. Educational institutions therefore have two jobs: to make their own work lighter in sensible ways and to equip learners to use AI competently and critically. A pedagogically sound approach frees up time for individual support, while careless use risks lower quality, data protection issues and unclear grading criteria.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Teachers in general and vocational schools
  • University lecturers
  • Trainers in adult and continuing education
  • L&D and corporate academy managers
  • Heads of school and programme directors

Typical challenges we address

  • Mixed-ability groups that need differentiated materials
  • Heavy workload for marking, feedback and documentation
  • Uncertainty about assessment and independent work in the age of AI
  • Unclear rules on which tools may be used with which data

What you will be able to do

  • You can build Make scenarios independently using triggers, routers, filters and data transformations.
  • You can process lists and records with iterators, aggregators and data stores.
  • You can integrate AI modules for classification, extraction and text generation into your processes.
  • You can safeguard scenarios with error handlers, validation and human approval.
  • Create differentiated teaching and learning materials with AI while safeguarding subject accuracy.
  • Develop assessment and task formats that deal sensibly with AI use.
  • Draft practical rules for privacy-compliant AI use in your institution.

Course outline

Day 1

Module 1 Fundamentals: scenarios, modules and data flow
  • Interface layout, scenario editor and execution history
  • Triggers, actions and searches: module types and their role in a scenario
  • Understanding bundles, mapping and data types and using them deliberately
  • Choosing between schedules, webhooks and instant triggers
Module 2 Logic: routers, filters, iterators and aggregators
  • Using routers and filters for branching and conditional flows
  • Splitting lists with iterators and combining them with aggregators
  • Applying text, date and maths functions to transform data
  • Using data stores and variables for interim values and duplicate checks
Module 3 AI building blocks in Make
  • Connecting language models via AI modules and provider integrations
  • Automating classification, structured data extraction and text generation
  • Building prompts from scenario variables and processing output as JSON
  • Combining AI agents in Make with tools and scenarios as actions
Module 4 Integrations, error handling and testing
  • Connecting common business applications and any API via the HTTP module
  • Applying error handlers such as Resume, Ignore, Break and Rollback
  • Validating AI output and routing unusable results to a person
  • Testing scenarios, optimising operations and documenting them for the team

Day 2

Module 5 Data protection, governance and operations
  • Assessing hosting region, data processing agreements and data flows to AI providers
  • Applying data minimisation and pseudonymisation within scenarios
  • Managing connections, teams and permissions across the organisation
  • Defining approval steps, monitoring and ownership for live operation
Module 6 Practice lab: Education & Teaching
  • Differentiating materials
  • Generating tasks and exercises
  • Preparing feedback
  • Course and module planning
  • Building learners' AI literacy
  • Communication and administration
Module 7 Data protection, quality & transfer to daily work
  • Pupil and learner data, grades and special needs information are highly sensitive and may only be processed in approved systems, ideally anonymised; national and regional education and data protection rules apply. Grading and examination decisions remain with educators, and AI use in assessed work must be governed by transparent rules.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Differentiating materials

From a source text, AI creates versions for different ability levels, language proficiency or support needs – with glossaries, guiding questions and extension tasks that the teacher checks and adapts.

Generating tasks and exercises

Practice questions, case studies, quizzes and model answers are created to match learning objectives and competence levels and can be imported into learning platforms. Variants for resits are easy to produce too.

Preparing feedback

Based on a marking rubric, AI drafts constructive, criteria-based feedback on anonymised work, which the educator adds to, weighs and takes responsibility for. Learners receive detailed feedback sooner.

Course and module planning

AI supports outline and lesson planning for teaching units, seminars or trainings, suggests changes of method and drafts module descriptions with clear learning outcomes. Timings and material lists are included.

Building learners' AI literacy

Educators design tasks in which learners use AI deliberately, verify its output and reflect on their process, rather than simply banning or ignoring AI use.

Communication and administration

Letters to parents, participant information, meeting minutes and FAQ answers are drafted faster, prepared in several languages and brought into a consistent tone. Key dates and deadlines are highlighted.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. Experience in teaching, training or education management; no technical background required.

Technical requirements

You will need a laptop with an up-to-date browser and a Make account; the free plan covers most exercises. API access for a language model is set up together during the course.

Data protection & compliance

Pupil and learner data, grades and special needs information are highly sensitive and may only be processed in approved systems, ideally anonymised; national and regional education and data protection rules apply. Grading and examination decisions remain with educators, and AI use in assessed work must be governed by transparent rules.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Bremen Request
  • Thu, 21 January 2027 – Fri, 22 January 2027 Salzburg Request
  • Thu, 4 February 2027 – Fri, 5 February 2027 Online Request
  • Wed, 10 February 2027 – Thu, 11 February 2027 Kaiserslautern Request
  • Wed, 24 February 2027 – Thu, 25 February 2027 Online Request

Frequently asked questions

Is Make the same as Integromat?

Yes. Integromat was renamed Make and substantially developed along the way. The core principle of visual scenarios made of connected modules remains, while a redesigned interface, many new integrations and AI building blocks have been added. If you used Integromat in the past, you will quickly feel at home and discover the new capabilities on the course.

How do I keep operation costs under control?

Every module that runs consumes operations or credits, and AI calls also use quota with the respective model provider. On the course you learn to design scenarios so that filters apply early, unnecessary runs are avoided and data is processed in batches. This keeps your automations economical and predictable as volumes grow.

Can Make be used in a GDPR-compliant way?

In principle yes, provided you set up the framework deliberately. This includes choosing the hosting region, signing a data processing agreement, reviewing connected AI services and applying data minimisation. On the course you work through these points with a checklist and learn to filter or pseudonymise sensitive data within scenarios.

Can I let AI mark my students' work?

AI can prepare feedback drafts on anonymised texts, but grading remains your responsibility. Names, marks and support information do not belong in unapproved tools. In the course we practise anonymising work, applying rubrics and critically weighing AI suggestions. Responsibility stays clearly with you.

How should I deal with AI-written coursework?

Bans alone fall short, and AI detectors are unreliable. More effective are formats that make process and reflection visible, such as oral components, learning journals or disclosed AI use. The course presents concrete task formats and policies that allow independent work to be assessed fairly.

How much does “Make for Educators” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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