Applied AI NL
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Year 2 · February

AI-driven Data Integration & Interoperability

AI is only as good as the data you can unlock: connecting systems, standardising them and making them work together.

Why this module

Why this matters

In every organisation, data is spread across dozens of systems. Every serious AI application therefore starts with integration: unlocking sources, connecting them and bringing them together reliably.

Interoperability — systems that speak each other's language through standards — makes your solutions future-proof. You learn to choose between integration patterns and to set up the connection securely as well.

What AI changes

How this subject itself is changing

Integration used to be schema work: figuring out field by field, by hand, what matches what. AI takes over most of that translation — a model infers the relationship between two sources faster than you can open the mapping document.

What takes its place is harder. Models also want the sources you used to leave alone: contracts, emails, minutes. And they place a new demand on your data — not merely readable by a system, but intelligible to a model, context and meaning included.

Content

What you will learn

Application

Directly in your own practice

You design the data integration for an AI application in your own organisation — from source to model.

Sources for an assistant

An information specialist unlocks three document systems into a single searchable knowledge layer.

CRM integration

A commercial analyst connects the CRM to an AI tool that flags sales opportunities — with proper authorisation in place.

Supply chain standard

A logistics employee introduces a single message standard with chain partners — and suddenly the forecasts do add up.

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 an integration design for a real AI application, including a security section.

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)