Training course · Make · Media & Journalism

Make for Media and Journalism

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 Media and Journalism” is designed for roles such as Reporters and editors in print, online and broadcast, News desk chiefs and section editors and Social media and audience teams and shows step by step how to use Make productively, safely and transparently in Media & Journalism – 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.

Newsrooms, publishers, broadcasters and content teams are caught between economic pressure and the demands of quality journalism. Generative AI is fundamentally changing research, production and distribution. It helps reporters work through documents and datasets faster, transcribe and summarise interviews, develop headline and teaser variants, adapt stories for different channels and make archives searchable. AI agents can sort wire copy or handle monitoring tasks. At the same time, AI raises core questions: how do you safeguard accuracy, how do you make AI use transparent to your audience and how do you respect copyright? Media professionals therefore need competence in both productive use and critical verification.

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?

  • Reporters and editors in print, online and broadcast
  • News desk chiefs and section editors
  • Social media and audience teams
  • Freelance journalists
  • Content and corporate publishing teams

Typical challenges we address

  • Intense time pressure alongside a growing number of channels and formats
  • Large volumes of documents, data and wire material
  • Safeguarding accuracy and credibility
  • Unresolved questions about copyright and labelling of AI content

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.
  • Use AI for research, transcription and production efficiently and faithfully to sources.
  • Check AI output systematically for accuracy and avoid typical pitfalls.
  • Apply rules on copyright, labelling and press ethics confidently when using AI.

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: Media & Journalism
  • Document research
  • Transcribing and analysing interviews
  • Headlines and teasers
  • Adapting formats
  • Unlocking the archive
  • Supporting fact-checking
Module 7 Data protection, quality & transfer to daily work
  • Press codes and journalistic due diligence apply unchanged: AI output must be verified and AI use made transparent to the audience in line with in-house guidelines. Copyright and related rights in source material and generated content must be respected, and source protection rules out entering confidential source information into unapproved tools.
  • 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

Document research

Lengthy reports, court rulings, budgets or leaked datasets are searched and summarised with AI and checked for relevant passages – every statement is then verified against the source.

Transcribing and analysing interviews

Audio and video interviews are transcribed, key statements and quotes are highlighted and sorted by topic, so stories can be written faster and quotes attributed precisely.

Headlines and teasers

For a finished story, AI generates variants for headlines, standfirsts, social posts and push alerts that match the brand's tone and from which the editors choose.

Adapting formats

An article is turned into newsletter summaries, explainers, podcast scripts or easy-read versions without changing what it says. Editors check every version for accuracy and house style before publication.

Unlocking the archive

Archive material is tagged, summarised and made searchable so that background, timelines and earlier coverage can be retrieved quickly. Dossiers on people, places and topics stay up to date with little effort.

Supporting fact-checking

AI helps identify checkable claims in texts, formulate verification questions and point out contradictions; the verification itself is done with primary sources. Due diligence becomes more systematic.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. Professional experience in journalism or editorial work; 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

Press codes and journalistic due diligence apply unchanged: AI output must be verified and AI use made transparent to the audience in line with in-house guidelines. Copyright and related rights in source material and generated content must be respected, and source protection rules out entering confidential source information into unapproved tools.

Suggested dates

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

  • Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
  • Mon, 7 December 2026 – Tue, 8 December 2026 Berlin Request
  • Mon, 14 December 2026 – Tue, 15 December 2026 Online Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Online Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Stuttgart Request
  • Mon, 1 February 2027 – Tue, 2 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.

Does AI-generated content need to be labelled?

That is determined by legislation, voluntary commitments and your organisation's guidelines. The EU AI Act sets transparency obligations for certain AI-generated content, and many newsrooms go further with their own policies. In the course we discuss when labelling is required and how to document editorial responsibility.

Can I use AI for fact-checking?

AI helps identify checkable claims and plan verification steps, but it is not a reliable source in itself. Language models can state false facts plausibly. Verification always relies on primary sources, documents and conversations. The course demonstrates a workflow that uses AI as an assistant without compromising rigour.

How much does “Make for Media and Journalism” 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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