Admissions status:
Open. The current round closes on October 15, 2025.| Course Details | Description |
|---|---|
| Level | Postgraduate |
| Degree | MS |
| Length | (1 year) or 6 terms (2 years) |
| Department | Department of Network and Data Science |
| US degree credits | 30 (1 year) or 60 (2 years) |
| Austrian degree ECTS credits | 60 (1 year) or 120 (2 years) |
Program Description
This master’s degree in Social Data Science is a full-time, interdisciplinary program offering advanced training in data science methodologies.
Social data science offers exciting opportunities for those who want to ask and answer new questions about human behavior and social processes in the digital era. You will learn to use mathematical, statistical, and computational tools to collect, curate, manage, and analyze massive datasets of human actions and interactions. You will blend Big Data and data science to design projects and digital experiments that shed new light on 21st-century social challenges, such as inequalities, climate change, migration, and technological disruption.
With an emphasis on critical thinking, practical application, and multidisciplinarity, you will develop an impressive portfolio of transferable skills to answer complex questions with data.
How the MS in Social Data Science Degree Works
Currently, the Master of Science in Social Data Science at CEU is offered as a full-time one-year program and a full-time two-year program.
- The one-year program (60 ECTS, 30 credits) builds on prior training in data science acquired during an undergraduate or graduate program. It is designed for students with a 4-years bachelor’s degree and/or demonstrable training in programming, statistics, machine learning and data science methods.
- The two-year program (120 ECTS, 60 credits) is open to applicants with a 3- or 4-year bachelor's degree in various disciplines, including social science, data science, physics, economics, environmental science, natural sciences, political science, sociology and computer science. Over two years, students receive advanced training in data science and social sciences while developing critical thinking skills to analyze large-scale human data.
Students of both programs choose one of the four offered specializations: Applied Social Data Science, Economics, Environmental Science, Environmental Science, or Political Sciences and Policy.
The courses of the MS program (one-year and two-year) are organized into four main modules:
- Mandatories
- Methods
- Specialization
- Electives
You will choose one of the four specialization tracks to match your professional and academic aspirations. You can choose from:
- Applied Social Data Science
- Economics
- Environmental Science
- Political Science and Policy
You will pick elective courses from a specific interdisciplinary list of courses related to your specialization, allowing you to explore diverse perspectives on your topics of interest. You will participate in a seminar series on current research and real-world applications of data science in academia and industry.
To put your skills into practice, you will complete research projects and a thesis in a topic related to your specialization. Students in the two-year MS in Social Data Science program will also complete a hands-on research internship at the end of the first year, which can be done in academic research groups or data oriented companies.
Expanding Your Expertise with Advanced Certificates
Advanced Certificates are student-only programs that enable you to dive deep into different subject areas through highly specialized training. This unique option offers you the possibility to tailor your learning experience at CEU according to your future academic and professional career.
We recommend the following certificate for students of MS in Social Data Science:
Who Is This Program For
This program is an entryway to becoming a new-generation social data scientist, entrepreneur, or policy maker. You will apply interdisciplinary thinking to complex issues that intersect society, technology, ethics, and politics. With the added advanced data science skills, you will extract critical insights from large volumes of data to arrive at solutions that make a difference.
Whether you step into the next chapter of your career or go on to pursue doctoral studies after graduating with an MS in Social Data Science, your proficiency in advanced data science methods and tools will be an asset.
Check If You Meet the Eligibility Criteria
To be accepted into the one-year program, you must have earned a first degree (bachelor's or equivalent undergraduate degree) of not less than four years of full-time studies with a minimum of 240 ECTS credits or equivalent.
To be accepted into the two-year program, you must have earned a minimum of 180 ECTS credits (or equivalent) during your undergraduate studies.
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, is a prerequisite for applying to the MS in Social Data Science. Bachelor’s level degrees in other fields will also be considered and evaluated individually.
You can find out more about the eligibility criteria for master’s degrees at CEU here.
Program-Specific Requirements
Below are the requirements for both versions of our MS in Social Data Science (one-year and two-years). Applicants to the one-year program need to submit additional documentation, please review the details below.
- Applicants must be in possession of a bachelor’s or higher 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.
- A degree in other fields will also be considered and evaluated individually.
- Applicants who are about to finish their degree can provide documentation indicating that they will earn their degree by the time of enrolling in MS SDS program.
- Applicants applying for the two-year master’s program must have collected a minimum of 180 ECTS credits (or equivalent) during their undergraduate studies, while applicants for the one-year master’s programs need a minimum of 240 ECTS credits (or equivalent).
Applicants to the MS in Social Data Science program should demonstrate their quantitative training by listing relevant mathematics, statistics, or data analysis courses along with the grades earned. This list should align with your submitted academic records.
Additionally, include short descriptions of projects you have worked on that showcase your ability to apply quantitative methods to social data challenges. Highlight the project objectives, your role, and key results to provide a clear picture of your quantitative skills in practice.
- All applicants are required to complete the free CEU Math Test after submitting their application to the program. The CEU Math Test (online) will take place within a week after the application deadlines. Applicants will receive an invitation to complete it and can see a sample test here.
- Proof of other relevant mathematics training during university studies will also be considered and evaluated — please list the courses and scores, which should match records in your submitted academic records, in a separate document.
- Provide the syllabi of the programming related course and the transcript which lists this course in your online application.
- An alternative is to complete the “Introduction to Programming” part under “Python Programming MOOC 2025" course offered by the University of Helsinki. This course is free and is an excellent resource to reinforce your programming fundamentals. In this case, please upload onto your online application a note in PDF format stating that you agree to provide the certificate of this course by March 30. Once you have finished the course, please send your result (the certificate and/or the scoring table) to sdsms@ceu.edu by March 30.
- Submit a maximum 2-page essay introducing your research topic on a quantitative topic and explaining your academic/professional background and your interest/motivation in interdisciplinary research. Indicate how further studies at CEU would help you achieve your future career goals.
- Submit a maximum 1-page statement to indicate and justify the specialization your choice of specialization for when you are a student in the MS in Social Data Science program. The possible specializations are Economics, Environmental Science, Political Science and Policy, and Applied Social Data Science.
- You may be contacted for an interview as part of the review process. The interview will be conducted online (Microsoft Teams).
- The interview is a conversation with our faculty, who want to assess your profile affinity with the program, and to give you the space to introduce yourself, explain your motivation for applying to the program, and ask any questions you might have.
- Proof of previous training in data science: Applicants must have solid previous data science training including knowledge in programming in Python, machine learning, databases, and applied statistics. They should submit the transcript which lists these courses in their online application.
- Applicants must have earned a bachelor’s degree of not less than four years of full-time studies with a minimum of 240 ECTS credits or equivalent.
What Awaits You
You will develop a high level of proficiency in applied data science methods from statistics, machine learning, web mining, network analysis, visualization, spatial analysis, natural language processing, and many more. Choosing one of four specialization tracks allows you to build expertise with in-depth seminars on topics that are relevant to your future career.
Specialization Tracks
A domain specialization within the MSc in SDS builds interdisciplinary fluency, preparing students to collaborate effectively with experts in the specialization domain. While not exhaustive, it equips students with essential concepts and tools for impactful, data-driven work in the chosen field. Applied Social Data Science is focused on methods.
Applied Social Data Science
- Agent-Based Models
- Text Analysis and NLP
- Social Networks
Economics
- Econometrics
- Sustainable Finance
- Economic Forecasting
Environmental Science
- Earth Observation in Monitoring SGDs
- Introduction to Geospatial Analysis
- Introduction to Geospatial Data Visualization
Political Science and Policy
- Big Data for Public Policy
- Impact Evaluation: Policy Applications with R
- Public Procurement Corruption and Analytics
One-Year MS in Social Data Science Program Overview
One-Year MS in Social Data Science Program Overview
- Mandatory courses
- Methods (mandatory elective courses from the module’s list)
- Courses from the list of your chosen specialization track
- Elective master's level courses from other programs at CEU
- Courses from the list of your chosen specialization track
- Elective master's level courses from other programs at CEU
- Thesis Seminar and Preparation
- Thesis Project
Two-Year MS in Social Data Science Program Overview
Two-Year MS in Social Data Science Program Overview
- Pre-Term:
- Pre-Term Courses (mandatory elective courses from the module’s list)
- Fall Term:
- Mandatory courses
- Elective master's level courses from other programs at CEU
- Winter Term:
- Mandatory courses
- Methods (mandatory elective courses from the module’s list)
- Academic Writing
- Spring Term:
- Research internship
- Courses from the list of your chosen specialization track
- Elective master's level courses from other programs at CEU
- Fall Term:
- Methods (mandatory elective courses from the module’s list)
- Courses from the list of your chosen specialization track
- Elective master's level courses from other programs at CEU
- Winter Term:
- Courses from the list of your chosen specialization track
- Elective master's level courses from other programs at CEU
- Thesis Writing
- Thesis Preparation
- Spring Term:
- Thesis Project
This program overview is provided as an example based on previous years' curricula. It is for informational purposes only and subject to change. Course offerings, schedules and content may be updated or modified at any time without prior notice. Please refer to official sources or contact the relevant department for the most current program details.
Program Accreditation
The Master of Science in Social Data Science at CEU is registered with the New York State Education Department in the United States and accredited by AQ Austria in Austria. CEU is accredited in the United States by the Middle States Commission on Higher Education (MSCHE).
Find out more about accreditation at CEU.
Your Instructors
See the full list of professors that are currently teaching in the program.
After Graduation
The MS in Social Data Science combines the best of two worlds: the curriculum will provide you with the most sought-after skills in the data science labor market. At the same time, CEU will give you the best place to learn about the most pressing societal or environmental challenges from world-class social sciences experts.
Employers increasingly value professionals who can extract meaningful insights from complex datasets while considering societal implications.
The MS in Social Data Science opens doors to careers at the intersection of data science, social sciences and policy-making.
Your Career Prospects
After obtaining an MS in Social Data Science, you may consider exploring roles with the following job titles:
- Data Analyst
- Data Engineer
- Business Analyst
- Business Intelligence Consultant
- Data Scientist
- Data Modeler
- Policy Advisor
- Data Science Specialist
- Government Analyst
- Financial Analyst
- Quantitative Analyst
- Statistician
- Research Analyst
- Geospatial Analyst
- Environmental Policy Analyst
- Data Journalist
- Data Manager
5 Reasons to Study Social Data Science at CEU
- Dual degree: Earn both an American and Austrian degree and expand your career prospects internationally.
- Develop a data-driven mindset: This program equips you with the skills to handle massive datasets and derive insights that address pressing 21st-century social challenges.
- Fast-track to an exciting career in data science: Master advanced computational skills for the collection, curation, processing, preparation, and analysis of data in your chosen specialization.
- Interdisciplinary approach: Gain a holistic perspective on complex social issues by combining data science with social science disciplines, such as economics, environmental science, and political science.
- Study in Vienna: For the duration of the program, you will be based in Vienna, which was named the world's most livable city for the third consecutive year in the Global Liveability Ranking by the Economist Intelligence Unit (EIU).
Contact Information for the Program
- Head of Department: Márton Karsai
- Program Director: Petra Kralj Novak
- Program Coordinator: Valeria Mora-Hernández
- Department: Network and Data Science
