& AI trainings

We offer trainings for both business leaders and AI professionals.

Research consistently shows that the biggest barrier to making impact with AI is not the technology itself, but the skills of the people. It is therefore crucial to invest in trainings which employ your people in the field of Data & AI.

Our Data & AI trainings have 2 target groups: the business and AI professionals. Business people are not building Data & AI solutions themselves, but need to understand how AI can make impact for their organization. They also need to be able to communicate about AI. AI professionals build Data & AI solutions and need both technical skills to do so as well as non-technical skills to collaborate effectively in teams with the business. 

The programmes for the two target groups look as follows:


AI for your organzation


Business program
AI for business

AI Professionals program
AI for professionals


Business program
AI Translator

AI Professionals program
Data Science Expert
Data Engineering Expert

Python and PowerBI

Many data analysis nowadays is carried out in Excel. Did you know you can speed up these analyses significantly by just applying the basics of the programming language Python? And that this typically is way less prone to errors? This course will help you by  not only learning basic data manipulations in Python, but also how to use these data to build your own dashboard in PowerBI.

Finding and selecting AI opportunities

This highly pragmatic course outlines a useful approach to identify AI opportunities for your organization. It will help you with identifying future AI opportunities which are both impactful as well as feasible to implement. It also guides to get a realistic impact estimate of a future project, which doesn’t underestimate the power of AI technology, but also doesn’t lead to hyping.

Classification models

How does a bank predict whether a customer will default on a loan next year yes or no? These questions are often answered by applying one the most well-known types of AI models: classification models. These models predict to which category/class a certain object belongs. In this course both the concepts behind classification models will be discussed, as well as some concrete examples of classification models, like: Decision Tree, Random Forest, XGboost and LightGBM.

Natural Language Processing

Natural Language Processing (NLP) models are all around us. Examples are Google Translate or ChatGPT. How can these AI models process such complex data as human text? That is the topic of this course. The course starts with discussing main applications of NLP, like clustering, categorizing and predicting. Then the process of how to structure unstructured data (mainly text) will be explained thoroughly. The course ends with a demonstration of valuable NLP algorithms, such as transfer learning algorithms.

Large Language Models

By the end of 2022 the AI model ChatGPT was launched. This disruptive technology affected many industries, since it often played the role of ‘know-it-all’ machine. Behind ChatGPT is a so-called Large Language Model (LLM). This is a language model which has been trained on billions of parameters and therefore may function surprisingly well in different contexts. This course will discuss the characteristics of Large Language Models, how to train and evaluate those models, and how to bring them to production. Lastly, it will highlight several innovative applications of Large Language Models, which participants can use to improve their own organizations.