Trust in AI starts with trust in data: measuring quality, improving it and governing it for the long term.
Garbage in, garbage out — and AI amplifies that effect. Poor data does not lead to a half-wrong answer, but to a wrong answer delivered convincingly.
Quality is not a project but a governance question: who owns which data, who decides, and how do you ensure it stays good? And conversely, AI in turn helps to guard quality.
Bad data used to be a reporting risk: a wrong number on a dashboard that somebody would eventually catch. Feed the same data to a model and you get no visible slip, but a fluent, convincing wrong answer — a thousand times a day.
The field widens at the same time. Models draw on documents, emails and minutes: material that never fell under data governance and that nobody owns. Quality control suddenly extends to everything the organisation has ever written down.
You create a quality and governance plan for a core dataset of your own organisation.
A data steward makes customer data quality visible in a dashboard — and puts it on the management agenda.
An information manager sets up ownership and stewardship for the five most important datasets.
An analyst trains a detection function that recognises anomalous input before it flows into the data warehouse.
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 is 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 on a daily basis.
You conclude each theme with a professional product or a technical solution addressing a real situation in your own work, which you discuss in an assessment with the lecturer. That 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 there is a quality and governance plan for a core dataset — measurable, with responsibilities assigned.
Email or call the programme — we will gladly help you think it through.