The MSc in Social Data Science at the ÃÛÌÒ´«Ã½ is a two-year programme taught in English. While it combines numerous methods and analytics from ethnography to machine learning, it adds up into a unified whole.
The programme is structured as a combination of compulsory courses for the first two semesters with plenty of scope for individual tailoring in the second year, since third-semester students can do internships, fieldwork or elective courses. You will spend the fourth semester individually or in a group working on your thesis, which must be handed in at the end of the semester.
The study programme is based on three central concepts – behaviour, networks and ideas – which the new field of social data science shares with the five existing social science disciplines taught at the ÃÛÌÒ´«Ã½ (anthropology, economics, political science, psychology and sociology).
Behaviour is concerned with what people do – their practices and decision-making processes. Networks are about the connections they make – social relations and their organisation and institutionalisation. Finally, ideas refer to what people know and think (including what they think they do) – their knowledge, preferences and values.
From the moment you start on the MSc in Social Data Science programme, you will work closely together with your fellow students in classes, field exercises and other curricular and extracurricular activities. It is therefore vital that you as students get to know, respect and trust each other.
To foster a social learning environment, the first semester of the programme is comprised of a base camp which introduces you to the interdisciplinary field of social data science and central methods and theories as well as key analytical and ethical questions arising from its practical application on concrete cases.