Sector 01
Manufacturing
200 learners, 267 workshop hours, 6 modules
On the shop floor, artificial intelligence is not a curiosity. It already sits inside machine control, quality inspection and maintenance planning. We teach people to work with that layer, not to build it. A graduate should understand what the system suggests, when to trust it and what to do when the suggestion is wrong.
What employers asked for
- Process automation, named by 45 per cent of surveyed companies
- Quality control and defect detection, 42 per cent
- Predictive maintenance, 38 per cent
Figures from the preliminary needs analysis carried out in January 2024 among 120 stakeholders in Poland, Czechia and Slovakia. The full needs analysis run inside the project reports in February 2027.
What the six modules cover
- Reading machine data and recognising when it drifts from the norm
- Vision systems in quality control: what they catch and what they miss
- Predictive maintenance, that is anticipating failures instead of reacting to them
- Working alongside a robot in an automated production cell
- The limits of trusting a system and the duty of human oversight
- Safety and accountability when an algorithm informs the decision
What a participant can do afterwards
- Read a predictive system's output and judge whether the alert is credible
- Explain to a supervisor what the system based its decision on
- Recognise when the algorithm is wrong and know who to report it to
Classes use real production line data shared by employers working with the partner organisations.
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