Training course · Make · Project Management

Make for Project Managers

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 Project Managers” is a hands-on course for roles such as Project managers, PMO staff and portfolio managers and Scrum Masters and agile coaches. Rather than learning Make in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Project Management.

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.

Project management is largely information work: clarifying requirements, building plans, assessing risks, reporting status and keeping a wide range of stakeholders aligned. Generative AI speeds up exactly these activities. It turns meeting notes into minutes and action lists, structures project charters and work breakdown structures, writes status reports for different audiences and supports risk workshops with well-grounded suggestions. AI agents connect project management tools, inbox and calendar and send automatic reminders about overdue tasks. Whether you work waterfall, agile with Scrum or hybrid, project leads gain time for what AI cannot do: making decisions, resolving conflicts and leading the team.

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?

  • Project managers
  • PMO staff and portfolio managers
  • Scrum Masters and agile coaches
  • Workstream and work package leads
  • Business teams with occasional project responsibility

Typical challenges we address

  • Heavy documentation workload for minutes, reports and plans
  • Many stakeholders with different information needs
  • Risks and dependencies spotted too late
  • Information scattered across tools, emails and chats

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.
  • Produce project documents such as charters, plans, minutes and reports faster and more consistently with AI.
  • Use AI as a sparring partner for risk analysis, planning and stakeholder communication.
  • Design simple automations for follow-up and reporting in your project environment.

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: Project Management
  • Meeting minutes and actions
  • Project charter and WBS
  • Audience-specific status reports
  • Identifying risks
  • Agile artefacts
  • Automated follow-up
Module 7 Data protection, quality & transfer to daily work
  • Project documents often contain confidential client data, contract details and personal data about team members, which may only be processed in approved AI environments. Analysing employee performance or workload data requires compliance with the GDPR and, where applicable, works council co-determination rights.
  • 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

Meeting minutes and actions

Notes or transcripts become structured minutes with decisions, open points and actions including owners and due dates, ready to be transferred into the project tool.

Project charter and WBS

AI helps turn a project idea into a charter with objectives, scope boundaries and success criteria, plus an initial work breakdown structure with work packages and milestones.

Audience-specific status reports

From raw data such as task progress, budget and risks, AI drafts status reports at different levels of detail – concise for the steering committee, detailed for the core team.

Identifying risks

In risk workshops AI suggests typical risks for the project type and industry, helps assess likelihood and impact and drafts mitigation actions. Owners and review dates are assigned straight away.

Agile artefacts

User stories with acceptance criteria, backlog refinement, sprint goals and retrospective formats are prepared with AI and then sharpened together by the team. Definitions of done can be drafted too.

Automated follow-up

AI agents check task progress regularly, remind owners about overdue items, summarise the week's changes and prepare a short project newsletter from them. The team stays informed without extra effort.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. Experience leading or contributing to projects, whether traditional, agile or hybrid.

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

Project documents often contain confidential client data, contract details and personal data about team members, which may only be processed in approved AI environments. Analysing employee performance or workload data requires compliance with the GDPR and, where applicable, works council co-determination rights.

Suggested dates

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

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Mon, 30 November 2026 – Tue, 1 December 2026 Munich Request
  • Thu, 10 December 2026 – Fri, 11 December 2026 Online Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Hanover Request
  • Mon, 1 February 2027 – Tue, 2 February 2027 Online Request
  • Thu, 11 February 2027 – Fri, 12 February 2027 Berlin 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 AI create a project plan?

AI provides a solid first draft of the work breakdown structure, milestones and dependencies if you describe objectives and constraints clearly. Effort estimates, resources and priorities still need to be agreed with the team. The course shows how to review AI drafts systematically and transfer them into your project tool.

Does this work in agile projects too?

Yes. In Scrum or Kanban, AI helps write user stories and acceptance criteria, prepare refinements and retrospectives and summarise sprint results for stakeholders. Decisions about the backlog and delivery naturally remain with the team and the Product Owner. AI supports, the team decides.

How much does “Make for Project Managers” 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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