Study Program

Master Data Science & Marketing Analytics

Erasmus Universiteit /  Rotterdam (NL)

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The programme combines courses from different disciplines into one coherent master’s specialisation that is focused on business applications. As no advanced prior knowledge is required, core courses in computer and data science lay the groundwork for the more advanced seminars. The latter explore state of the art machine learning methods and apply them to real-life business problems. 
This master’s specialisation consists of core courses, seminars, electives and a master's thesis distributed over 5 blocks of 8 weeks. In the first block, 3 core courses of 4 credits will each introduce you to the broad range of both knowledge and skills that you will acquire and perfect in the Master Data Science and Marketing Analytics. 

Interactive seminars are a very important component of our programme. You will be involved full time in a seminar for an entire block, allowing you to dive deep into the material, guided by the lecturers. For these intensive courses, active participation and strong commitment is a must. The second and third block follow this format, starting with a focus on learning new methods, followed by a seminar devoted to solving business problems, putting the methods and skills obtained in earlier blocks to the test.

In the fourth block you will follow one final course and choose one elective. 
You should already start thinking about your master’s thesis in the spring, but block 4 and 5 will be dedicated entirely to this task, which is based on research you have conducted yourself under supervision by a member of our academic staff. Erasmus Research & Business Support (ERBS) offers job market preparation sessions in block 5. 

The curriculum consists of:

  • 50 % computer science/machine learning 
  • 50 % marketing business 

In class

The key strength of machine learning techniques is their predictive ability. For marketing analysts this opens up many opportunities to improve customer experience, making shopping both more pleasant and effective, for example by providing accurate recommendations. Interesting business cases that will be covered include the composition of a set of relevant products, but also the identification of the customer’s stage in the buying process, allowing firms to provide the information that is most valuable at that stage to the customer.

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