AI training for manufacturing
Production teams generate data every day, but few people have learned to ask questions of it and find answers. Analysis requests pile up on a handful of people.
▶ The solution
AI literacy for executives; Python, data analysis, statistical thinking, machine learning and deep learning for technical teams. Hands-on, and tailored to your team's level and your own data.
▶ Use case
Planning, quality and maintenance teams learn to analyze their own downtime and scrap data in Python. By the end, each team presents a small piece of work answering its own question with its own data.
▶ Data you need
An anonymized sample of the company's own data is enough: production records, downtime, scrap and quality measurements.
The industry's data landscape
In manufacturing, data usually lives in the ERP (orders, stock, purchasing), in production tracking (downtime, scrap, shifts) and in quality records. These systems rarely talk to each other; even the same product can carry different codes in each. So the first job is often to bring them together in one table.
Corporate training gives your team the knowledge to do data and AI work without depending on outsiders. There are two audiences: executives, who need to tell what is possible from what is hype, and technical teams, who will do the work themselves.
The math behind it
Precision = TP / (TP + FP) · Recall = TP / (TP + FN)
- TP: cases the model correctly flags
- FP: cases it flags by mistake
- FN: cases it misses
How I work
- Before
Level and goal.
The participants' current level, and what they should be able to do afterwards, is made clear. Executives and technical teams get separate goals.
- Preparation
Content and examples.
The programme is shaped around the team's level. Examples and exercises are chosen close to the company's real problems.
- Training
Hands-on sessions.
More practice than lecture: participants write code, work with data and interpret results. Questions are answered through the company's own work.
- After
Back to work.
A concrete task or project proposal the team can apply right after. Where the learning will be used is clear from the start.
▶ Questions and answers
AI training for manufacturing — what data do you need?
An anonymized sample of the company's own data is enough: production records, downtime, scrap and quality measurements.
When is this the wrong choice?
The training is just a line in the annual plan. A training nobody will apply afterwards produces nothing but certificates. You actually need a project. If the work needs to get done soon, doing the project may be faster than training the team.
How does this work start?
With a short intro call. I listen to what you need and tell you plainly whether your data is enough for the job and what the first step should be. I reply to every message within 24 hours.
▶ Concepts
Linked to Wikipedia and Wikidata.
▶ Sources
- [1]Wikipedia, Precision and recall, 2026-10. en.wikipedia.org/wiki/Precision_and_recall
▶ Intro call
Let's talk about your situation.
In a 30-minute call I listen to what you need and tell you plainly how I can help.
Book an intro call▶ In other industries