Applied Data Science

Organizations do not always have the specialized knowledge needed to fully exploit the latest technologies, or the time to develop that specialized knowledge themselves. Data scientists of the future can play a role here.

In recent years, more and more organisations have embraced the potential of data (science). At the same time, the field is developing at lightning speed, and we see technology such as Large Language Models being rapidly adopted. However, organizations do not always have the specialized knowledge needed to fully exploit the latest techniques, or the time to develop that specialized knowledge themselves. Data scientists of the future can play a role here.

Within the Applied Data Science master program at Utrecht University, concluding research is an important component. Here, students work in teams on a data project, preferably in collaboration with an external social partner. The issues here range from complex analyses on already prepared data to dealing with missing data and everything in between.

What did the collaboration entail?

A team of 2 or 3 students will work full-time for 10 weeks on an external party's research question, with the teams being supervised from the university by our researchers and a thesis coordinator. They help formulate an appropriate research question. In addition, it is important that the client also has data expertise in house and can give direction to the research during the bi-weekly team meetings. The students develop the research question into an independent and high-quality study. This always works toward directly applicable results for the organisation. The processed data and the research are described in such a way that the results are also suitable for reuse in a follow-up project by the own organisation or with a new student team.

Goal of collaboration in education

The collaboration between students and external community partners is relevant to both. The students get to work with real data and get the opportunity to put their knowledge to use. At the same time, external social partners benefit from the expertise the students bring with them, receiving directly applicable results.

(Intended) result

The topics students work on and the resulting results are very diverse. In previous years, students have conducted research for various agencies. For example, they have conducted research for municipalities on the automatic processing of objections against established WOZ values of houses. They have also supported the Dutch Food and Consumer Product Safety Authority (NVWA) in further developing their commercial software, which can predict the relative likelihood of animal welfare violations on farms. For Planalogic, students looked at using data to design affordable and sustainable housing. In addition to these examples, students also successfully collaborated with several other external community partners.