Working iteratively in multidisciplinary teams: planning, prioritising and delivering in short cycles.
AI projects are uncertain by definition: you don't know in advance exactly what the model can do. Working iteratively — starting small, learning fast, adjusting course — is the way to manage that uncertainty.
Almost every organisation works agile. Because all projects in the programme are carried out using Scrum, the rhythm of sprints, reviews and retrospectives becomes second nature to you.
The sprint was invented because building was slow: you cut a long project into chunks you could oversee. Now that a working prototype takes an afternoon, building is no longer the bottleneck — and the rhythm loses its original reason for being.
What replaces it is a cadence of decisions: how often can you learn, validate and adjust? On top of that, part of your team is not human. Backlog, definition of done and review all change once an agent picks up the task.
You carry out all projects in the programme using Scrum — in teams, with sprints and deliveries.
Your project team delivers working functionality every two weeks and demonstrates it to the client.
You learn to say no: what moves to later because it adds less value right now?
Every sprint, your team demonstrably improves itself on one point.
You take this module the way you take the whole programme: classes every other week on Friday and Saturday, with a study load of 15–20 hours per week, of which 10–15 hours are self-study. The teaching is a mix of classroom lessons, practice-based learning, blended learning and working groups or study teams — taught by lecturers who practise the profession themselves every day.
You conclude each theme with a professional product or a technical solution based on a real situation in your own work, which you discuss in an assessment with the lecturer. This way your portfolio grows with real work — and your employer benefits directly.
The format is not new: the teaching approach and the AI modules have been running for three years at the AI Proeflokaal — with business, with government, and across part-time modules and minors. What you meet in class here has already been worn in elsewhere.
By the end, working in agile teams comes naturally to you — and you can get one going yourself.
Email or call the programme — we're happy to help you think it through.