How to follow, forecast and control the spreading of a pandemic? How can we use data to improve and inspire decisions that could lead to positive changes in our societies? How could we use new technologies to achieve larger participation of people in the decision-making processes?
From understanding how the internet influences our world to forecasting and controlling the spread of a pandemic, we need data science experts who are ready to face the new societal, organizational, and environmental challenges.
Our interdisciplinary MS program in Social Data Science prepares you to better understand our digital societies and contribute to shape their future. As a social data scientist, you will combine data analytic skills with a socially responsible and critical lens to question the inequalities, ethical challenges, and organizational power that develop our society.
Who are we looking for?
Our 1-year and 2-years MS in Social Data Science programs are directed to applicants with a bachelor’s degree in one of a broad range of disciplines, including social science, data science, physics, economics, environmental science, natural sciences, political science, sociology, and computer science. Applicants with a degree in other fields will also be considered and evaluated individually.
Why should you pick our program at CEU?
- Depending on your prior training in data science, choose between a 1-year or 2-years MS in Social Data Science Program.
- Study in English and live in Vienna, Europe’s new international business hub.
- High quality degree, fully accredited in Austria and the U.S.
- Develop your skills via one of our 4 specializations:
- Applied Social Data Science
- Economics
- Environmental Science
- Political Sciences and Policy
- Conduct exciting research internships in research teams, companies, and international organizations.
- Over 76% of master’s degree CEU graduates are employed in the first 6 months after graduating.
- We are committed to promoting the values of an open society, self-reflective critical thinking, and academic freedom.
To see the list of application requirements, deadlines, and instructions on how to apply, please visit How to Apply
2-years MS in Social Data Science (120 ECTS, 60 credits)
The 2-years program offers the full-time multidisciplinary curriculum for you to become a social data scientist.
During our 2-years MS in Social Data Science, you will gain core and advanced methodological training in data science and social sciences, while also developing your critical thinking skills to work with massive data sets of human actions and interactions. Additionally, you will focus your research and studies in one of the four specialization fields of Applied Social Data Science, Economics, Environmental Science, or Political Sciences and Policy.
In the two-year program, you will master contemporary computational skills for the collection, curation, processing, preparation, and analysis of data. You will develop a high level of proficiency in methods from applied statistics, machine learning, web mining, network analysis, visualization, spatial analysis, natural language processing, and more.
How to Apply to the 2-years MS in Social Data Science
Program structure and course list 2024/25 (2-year program)
1-year MS in Social Data Science (60 ECTS, 30 credits)
Did you already complete or are about to finish your training in data science during your undergraduate or graduate studies?
Our 1-year MS in Social Data Science is a program specially designed for you. It is directed to students with a 4-years bachelor’s degree and demonstrable training in programming, statistics, machine learning and data science methods.
During the 1-year MS in Social Data Science you will optimize your data science skills and receive focused training in one of the four specialization fields of Applied Social Data Science, Economics, Environmental Science, or Political Sciences and Policy.
How to Apply to the 1-years MS in Social Data Science
Program structure and course list 2024/25 (1-year program)
Study Plan and Specializations
Beyond becoming an expert in social data science, you will be able to choose among four specializations that we offer.
Do you strive to become a data science professional or an entrepreneur in the social data industry? Our professional specialization in Applied Social Data Science is perfect for you.
Or perhaps you envision your future in academic research? Then an academic field like Economics, Environmental Science or Political Science and Policy could be the right one for you.
Are you curious about some of the courses you will enjoy while studying at CEU? You can find the detailed curriculum of our MS programs here.
Here is a sneak peek:
Tuition, Scholarship and Internship Programs
The MS in Social Data Science tuition fee is €12,000.
Access to education is one of CEU’s core values. It guides us in setting as affordable tuition fees as possible - without impacting the quality of the education we provide. Each year CEU offers talented master’s students generous, merit-based, partial tuition awards and scholarships through Financial Aid to help them focus on their studies.
Study in Vienna, the Heart of Europe
The Social Data Science program is a Master of Science degree program simultaneously accredited in the U.S. and Austria, providing a degree with both accreditation at once. Join CEU, a leading research institution in social sciences in Central Europe where students work under close supervision and enjoy the support of world-class researchers. We are committed to promoting the values of open society, self-reflective critical thinking and academic freedom. You will study in Vienna, the capital of music, a new business hub of Europe and, according to the Economist Intelligence Unit, the world’s most livable city.
Do you want to learn more about the MS SDS program? |
Do you want to apply to the MS SDS program?Learn more about the detailed application guidelines, admissions information, and the application checklist. |
Do you have any question? |
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Associate Professor Program Director of MS SDS |
Associate Professor Head of Department, DNDS |
Professor |
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Teaching: Data Mining and Big Data Analytics |
Teaching: Digital Data Collection Methods |
Teaching: Social Networks 1 |
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Program Coordinator of MS SDS |
