Applied AI NL
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Year 4 · November

Project Assignment: Data Science and Data Management Implementation

AI Classic Makers

Everything comes together: a data science solution with the accompanying data management, actually implemented at an organisation.

Why this module

Why this matters

This is the dress rehearsal for your graduation: proving that you can work end-to-end — from a client's question to a working, validated model in use.

The assignment is deliberately integral: model and data and frameworks and people. A model that nobody uses or nobody can explain does not count.

What AI changes

How this subject itself is changing

The model is up faster than ever, which is precisely why it no longer counts as an achievement. Delivering a validated model was the whole project ten years ago; now it is the starting point after which the work begins.

What you prove here is that it holds on data you checked yourself, that it is used by people you brought along, and that you can explain to a client why the decision coming out of it can be defended.

Content

What you will learn

Application

Directly in your own practice

You carry out the assignment in your own organisation or for an external client — with real users and real data.

Your own organisation

A participant implements a demand forecast, including data pipeline, at their own employer.

External client

A pair builds a capacity model for a healthcare organisation, including quality assurance of the source data.

Handover

Every assignment ends with a working model, documentation and a trained administrator.

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 project assignment you have an implemented data science solution plus implementation dossier to your name.

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)