After go-live the real work begins: managing, monitoring and further developing AI applications in a controlled way.
Models age, costs mount, usage changes. Without proper management, every AI application dies a quiet death — or worse: it keeps running while no one knows any longer whether it is still correct.
Managing AI is a discipline in its own right: alongside classic application management, you monitor model quality, data flows and cost per use. And here too, AI itself helps out — with detecting, summarising and resolving issues.
You draw up a management plan for an existing AI application and set up the accompanying monitoring process.
A functional administrator arranges ownership, an update process and quality monitoring for the customer service bot.
A team lead makes gen AI costs visible per department and adjusts course before the bill explodes.
A data engineer sets up the cycle by which the predictive model is refreshed every quarter in a controlled way.
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.
After this module you have a management plan plus a fully set-up monitoring process for a real AI application.
Email or call the programme — we're happy to help you think it through.