Understanding Machine Learning
A day on machine learning and large language models: what these systems can do, how they arrive at their results, and what that means for your work. The workshop builds understanding and judgement, not product training. You need no prior knowledge.
- Group
- 2-8 people
- Duration
- 7,5 hours
- For
- Decision makers & practitioners
- Focus
- Making sense of language models
- Scope
- 1 person-day
Schedule of the day
It starts with the foundations: how a model learns from examples, what a large language model is, and what role prompts play. We then look at concrete AI tools, their fields of application and their limits. The third part is the critical view: where results are reliable, where they are not, and which tools are better avoided. The day closes with practical exercises on scenarios from your own field of work.
Result
An assessment of which tools suit your tasks and which do not, along with approaches tested in the exercises. Afterwards you can judge where using them makes sense and where restraint remains in order.
Requirements
No prior knowledge of machine learning or AI. What it takes is a willingness to engage critically with the tools, and active participation: the day lives on trying things out, not on listening. It is meant for managers, IT professionals and project leads.
Not suited for
Anyone who wants to train models or implement systems is in the wrong place: the workshop builds understanding, not development. And anyone looking for training in a single product will get more breadth here than they need.
Related
Request this workshop
Scope: 1 person-day on site. Preparation and follow-up come on top and depend on the format; I will name the effort in our first conversation.