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Full time September MSc Full-time: 2 years

About the course

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Learning how to turn real-world data sets into tools and useful insights, with the help of software and algorithms.

Data plays a role in almost every scientific discipline, business industry or social organisation. Medical scientists sequence human genomes, astronomers generate terabytes of data per hour with huge telescopes and the police employ seismology-like data models that predict where crimes will occur. And of course, businesses like Google and Amazon are shifting user preference data to fulfil desires we don’t even know we have. There is therefore an urgent need for data scientists in whole array of fields. In the Master’s specialisation in

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Entry Requirements

1.A completed Bachelor's degree in Computing Science or in Artifical Intelligence or related area. For the specialisation in Data Science, we also encourage students to apply with a background in natural sciences, such as Chemistry, Biology, and Physics, who also have a keen interest in data analytics and proven mathematical and programming skills.
2.A proficiency in English:
a.A TOEFL score of ≥575 (paper based) or ≥90 (internet based)
b.An IELTS score of ≥6.5
c.Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE) with a mark of C or higher


Fees

€2,143 (from EEA countries); €12,645 (from non-EEA countries)

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Student Profile(s)

Willem and Frank

Frank: "I wasn't entirely sure whether I wanted to carry on studying. I generally prefer practical work, but my curiosity got the better of me. I registered at the university and gave myself six months to see if this was for me. After this period, I decided to stay on and I gradually felt more and more at home. Computing Science is such an exciting subject - it's constantly evolving."

Willem had completed two internships during his four years of study, but he felt that he was not ready to start working full-time yet. "The Master's programme is great. It's so different from what we did before. There's a lot of freedom here, everything is small-scale and it's easy to interact with the professors. Most of the courses are not standard, and some of the professors even change the content of their courses halfway through if they notice that the students' interest is moving in a different direction." Frank: "They encourage us to get off the beaten track, both in education and in research. In fact, it's basically up to you to decide what to do."

For their Master's research, Frank and Willem started working on the static structure of the Internet. "With research you never know where it will lead," says Frank. "I ended up focusing on web communities and the way in which you can see which sites belong together on the basis of their structure. I analyse these clusters and monitor them, in order to see how they evolve. This could be of interest to advertisers, for example."

Willem took a different path. He looked at optimising interest in websites. "When people position their site on the Web, they want to know where it will generate most interest. I devised a way of ranking this interest, so that people can optimise their location and thus optimise the volume of traffic to their site. Initially, I didn't expect that my research would attract so much attention. But, when I submitted an article based on my Master's thesis to the International Conference on the Theory of Information Retrieval, which was organised by Microsoft Research and Cambridge University, it was accepted. Microsoft and co-sponsor Yahoo are now very interested in my work. It's great when your ideas catch on, and you get serious interest from some of the biggest companies in the world."



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