"When I was applying for master’s programs, it was the excellent education that put this programme at the top of my list. It was the department's unique community which led me to not want to apply anywhere else. The wonderful community, made up of students, teaching and support staff and MSV Incognito (the study association), is what sets this place apart. Whether you want to discuss a topic, set up an event or just want help in solving question 2B, there’s always someone you can ask. It’s through the community that I’ve been able to develop and apply useful skills I learned in class and outside of it, whilst also developing friendships and career connections. You’re free in how much you wish to participate in the community, safe in the knowledge that it’s there for you when you need it."
Other testimonials
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The theoretical knowledge I gained from the programme is something I would never have learned on the job.
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The decision to continue my studies in Maastricht was obvious because I love both the city and the university. Additionally, I have a strong affinity for Maastricht University's project-based learning approach.
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I love living in Maastricht. The people are warm and friendly. As a member of one of the student associations, I truly enjoy the city's student life. In my spare time, I sail with the sailing association, climb, and read about new developments in data science and artificial intelligence.
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I learn a lot through practice, and the more hands-on experience, the better!
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The Data Science for Decision Making master's programme sits on the crossroads of Data Science, Applied Mathematics/Operations Research and AI.
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Maastricht is such a vibrant student city. Students are everywhere! There are also so many bars and pubs that there is a cosy place for everyone
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The Department of Advanced Computing Sciences of Maastricht University has been doing research since 1987; surely 35 years ago not many people knew what Artificial Intelligence was. The experience of this department is why I came to study my bachelor’s in the first place.
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I see myself working in research, using my cultural background to integrate teams working all around the globe. Investigating state-of-the-art techniques and methods to help solve problems that we might not even know exist yet.
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We do lots of brain storming, write some code or set up some math. We get regular advice from the project supervisor. Sometimes the advice is very helpful. Other times it is not helpful.
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A very nice place in my faculty is the Swarmlab, where you get access to equipment you don’t usually have.