Applied AI NL
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Year 3 · September

AI-driven Data Modelling

Data models that support AI: from conceptual model to scalable, documented implementation.

Why this module

Why this matters

A good data model is a quiet win: data becomes reusable, integrations become simpler and AI applications get a stable foundation. A bad model is paid for over years in custom workarounds.

What's new is that AI itself now helps: generating, documenting and testing models. You learn to model with that help — but with the craftsmanship to judge the result.

What AI changes

How this subject itself is changing

Drawing the model, normalising it and documenting it was patient work that took days. An AI proposes it in minutes, explanation included. The skill that remains is not drawing but judging: does this model match how the organisation actually works?

At the same time a layer appears that classic modelling never had. A language model needs no key but meaning: concepts, relations, embeddings, knowledge layers. Modelling becomes less about storage and more about semantics — recording what something is.

Content

What you will learn

Application

Directly in your own practice

You model a domain from your own organisation — including validation with the people who use the data every day.

Customer 360

A CRM administrator models a single customer view across four systems — the basis for every next AI step.

Data mart

A controller designs a star schema that takes reporting from days to minutes.

Knowledge model

An adviser structures the conceptual framework of his field so that an assistant can reason with it reliably.

How you work

Learning alongside your job

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.

After this module you deliver a widely supported data model for your own domain, validated with the business.

Questions about this module?

Want to know if this suits you?

Email or call the programme — we're happy to help you think it through.

onepager for students (pdf) · onepager for employers (pdf)