Current facets (Pre-Master)

Equal Shares of Data Science and Marketing courses

The curriculum of the master specialisation Data Science and Marketing Analytics consists of roughly equal shares of data science and marketing courses. 

Block 1

The programme starts with a course “Introduction to programming” and a course “Business analytics”. These two courses are supplemented by the course “Strategic Marketing Decision Making” to introduce statistical techniques commonly used in Marketing.

Block 2

In the second block, students take the seminar Data Science. In this seminar, state-of-the-art machine learning methodology is introduced along with essential data preparation and collection skills to conduct valuable analyses. The seminar puts a strong emphasis on application of the methods in ‘R’ rather than focusing on underlying statistical theory. Students have to actively participate in the seminar through presentations, written reports, group discussions and applied projects where machine learning techniques are applied to real world cases. Successful participation in the seminar enables students to gather and process complex data structures by selecting and executing appropriate tools. 

Block 3

In the third block students choose, depending on their personal goals and preferences, a marketing seminar focused on customer analytics, customer relationship management, consumer channel dynamics, or supply chain management and transportation.

Block 4: Thesis and elective courses

In block four, students start working on their thesis whilst completing one elective course in marketing or economics and a final data science course: “Advanced marketing and media analytics”. In this course, an overview of the latest and most advanced machine learning methods, with an emphasis on prediction for marketing (such as sales, communications, usage, etc.), is given. Once again, the focus in this course will be on application rather than on mathematical/statistical rigor.