‘The level of this master is similar to university masters, but you get more hands-on experience’

After his university bachelor in biomedical sciences, Koen Timmerman decided that he wanted to learn more about bio-informatics and data science. He heard good stories about the master Data Science for Life Sciences, so he decided to enroll.

'I started out in biomedical sciences at the University of Groningen, but gradually discovered that I also like programming. So for my bachelor thesis I chose a subject that was related to bio-informatics, and my supervisor mentioned the Data Science for Life Sciences master as a possible next step. He had experience with students from this master and recommended it highly, so it seemed like a good choice!

So far, I think I have made the right step. It is a lot of programming, I haven’t used my biology knowledge that much yet. If you consider this master, it might be good to brush up on some basic programming beforehand. I do have to work hard to keep up with the students who did a programming based bachelor. But I’m not the only one who has to catch up, and the teachers and other students help me a lot. It is a challenge, but a good one! I really like learning all the techniques and programming languages. And it may sound weird, but I also really enjoy the math classes we get.

I thought a master at the Hanze might be easier than a master at a university, but I think the level is quite similar. The biggest difference is the way the lectures are scheduled. At the university, you have classes for a few hours a day where you just listen to the teacher. Here, we are much more encouraged to get to work, even during classes.

My favorite part of the master are the group projects. It is really fun to think of a plan together with the other students, and then execute it. We get a lot of freedom to follow our own interests and things we want to research further. For instance, we researched a TikTok video that claimed that eating kiwi before going to bed helps you sleep better. We tried it ourselves and collected data, but it turned out to be wrong.

I think all the projects and the way of working really helps you prepare for the workfield. We get a lot of hands-on experience and already use most of the things we learned, so it is easier to adapt and see how the data science techniques might benefit certain situations. I think that will be very beneficial when I graduate!'