Master in Computational Social and Political Science
Milan, Italy
Master degree
DURATION
2 years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
TUITION FEES
STUDY FORMAT
On-Campus
* application for matriculation: from 17/09/2025 to 24/09/2025
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Key Summary
The Master's Degree Programme in Computational Social and Political Science (CSPS) equips students with the knowledge and competences needed to provide empirically-grounded and theoretically-informed explanations of political and social phenomena, applying computational and quantitative methods of analysis to quantitative and qualitative data. Entirely taught in English, the program combines the hypothesis-driven deductive approach typical of the social sciences with the inductive approach of data science, enabling students to develop a robust conceptual, methodological, and practical repertoire for empirically grounded analysis of social and political phenomena.
Graduates are able to conduct projects in social and political research, with observational or experimental research designs, with the aim of testing theoretically-grounded hypotheses, exploring aggregate phenomena and trends, and developing evidence-based proposals for political and social interventions. Students work with primary survey data, digital data (including social media data), and secondary data, including numerical and textual data, to be collected, managed and analyzed using statistical or computational models, large language models, machine learning, and statistical learning techniques. By integrating attention to theory, qualitative data and factors, and advanced computational techniques, students are stimulated to develop a mindset for causal inference and fine-grained detection of generative, causal mechanisms driving complex socio-political outcomes, including collective opinions, social dynamics, and political trends.
Throughout the Programme, students receive extensive, integrated, and cutting-edge training in analytic methods, statistics, and computational science. Students are equipped with solid methodological foundations by means of a compact training on different designs for social research and policy analysis, and evaluation. The focus is on survey, experimental, and computational approaches, and will be supported by appropriate foundations in computer programming and data management, including related ethical and legal issues. Course topics include state-of-the-art techniques in multivariate analysis, machine learning, text-as-data, social network analysis and network science, causal inference, and agent-based computer simulation models. Epistemological frameworks, disciplinary theories and qualitative insights and data from the field are incorporated as the context supporting an informed use of each modelling technique.
The courses include a substantial amount of practical training, as well as individual and group project activities, closely connected with real-world data and case studies. The teaching methods aim to foster the methodological posture of computational social and political scientists, enabling students to approach the analysis of political and social phenomena starting from the formulation of relevant, empirically testable hypotheses, linking phenomena to models, designing consistent procedures for data collection and evidence mapping, and evaluating the implications of results in terms of strategic political decisions, intervention and evaluation.
The Programme requires the attainment of 84 credits from compulsory exams, including 27 credits from courses on observational and experimental designs for computational political and social research, 6 credits in computer science methods for large language models, 6 credits on ethical and legal issues related to data and computational analyses, and 45 credits on computational and statistical models for survey, digital, network, and text data. In addition, students acquire 12 credits from other additional elective and optional activities, 9 credits from internships (6 for students who need to earn 3 ECTS for Italian language A2), and 15 credits for the final thesis are provided.
Regional Scholarships
Regional scholarships provide both financial support (from a minimum of €1,296 to a maximum of €7,316 ), exemption from the second tuition fee installment and free access to university canteen services.
These scholarships are awarded through a competitive selection process to students who meet specific merit, income and enrolment requirements, and who are regularly enrolled in a University of Milan programme.
The call for applications is usually published in July. For more information, please visit: Regional scholarships | Università degli Studi di Milano Statale
MAECI Scholarships
Each year, the Italian Ministry of Foreign Affairs and International Cooperation (MAECI) offers scholarships to international students and Italian citizens living abroad (IRE).
These scholarships aim to foster international cooperation in cultural, scientific and technological fields, promote the Italian language and culture, and support Italy’s presence worldwide.
The call for applications and the list of eligible countries are available at: Study in Italy.
European Futures Scholarships
The University of Milan offers 30 scholarships worth €10,000 each to talented students from the European Union who have completed a bachelor’s degree by 31 July and wish to enrol in a master’s degree programme for the 2026/2027 academic year.
The scholarship package includes:
- full exemption from tuition fees
- 30 free places in shared twin rooms in university halls of residence
- participation in the UniMi Ambassadors programme, engaging outstanding students in international promotion activities (e.g., campus tours and webinars)
Applications are open from 5 May to 15 June 2026. The Call and the application link are available here: International scholarships | Università degli Studi di Milano Statale
Year 1
Compulsory
- Advanced Multivariate Analysis
- Data Governance: Ethical and Legal Issues
- Foundations of Statistical Modelling for Social and Political Sciences
- Policy Design
- Programming for Social Data Science
- Research Design & Experimental Methods in the Social Sciences
- Survey Methods for Public Opinion Research
Optional activities and study plan rules
1 - Students must earn 6 credits/ects for Elective substantial course
Year 2
Compulsory
- Agent-Based Modelling
- Causal Inference in Social and Political Science
- Social Network Analysis
- Text Analytics and Machine Learning and Large Language Models
- Final Exam
Optional activities and study plan rules
2 - Students must earn 6 credits/ects for Elective substantial course
3 - Italian students or students with a certificate in Italian at level A2 or above must acquire 9 ECTS from an internship in the private sector, in government or public administration organisations or in academic institutions (including departmental laboratories and centres). Students who do not have a certificate in Italian at level A2 or above must acquire 3 ECTS of Italian language provided by the University Language Centre (SLAM), which reduces the ECTS for an internship to 6 ECTS.
The University of Milan ranks among the leading institutions worldwide. In the QS World University Rankings 2027, it is ranked 270th globally, confirming its steady progress on the international stage, having gained six positions compared to the previous year despite the increase in the number of universities evaluated.
The University’s excellence is particularly evident in subject rankings. According to the QS World University Rankings by Subject 2026, the University of Milan is placed among the top 50 in Veterinary Medicine and it’s in the top 100 universities worldwide in five disciplines:
- Anatomy & Physiology
- Medicine
- Philosophy
- Pharmacy & Pharmacology
- Sociology
The University also ranks among the top 150 worldwide in several subjects, including:
- Agriculture & Forestry
- Classics & Ancient History
- Law
- Politics & International Studies
- Social Policy & Administration
- Modern Languages
- Dentistry
- Nursing
Moreover, it is placed within the top 200 globally in a broad range of disciplines:
- Archaeology
- Chemistry
- Communication & Media Studies
- Data Science & Artificial Intelligence
- Geography
- Mathematics
- Natural Sciences
- Physics & Astronomy
- Statistics & Operational Research
The University of Milan also stands out for its strong commitment to sustainability, ranking 4th in Italy and 174th globally in the QS Sustainability Ranking—an impressive rise of 45 positions. This achievement highlights the University’s growing impact in addressing key social and environmental challenges, reinforcing its role as a forward-looking and responsible institution.
This advancement reflects a comprehensive strengthening of the University’s sustainability policies. Particularly noteworthy are the results in the Social Impact dimension, which highlight increasingly effective initiatives in inclusion, knowledge exchange, and social responsibility, as well as in Governance, with high standards of transparency, ethics, and institutional accountability.
Overall, these results confirm the University of Milan as a multidisciplinary public institution capable of combining academic excellence, social impact, and a strong commitment to sustainable development.
The CSPS Programme trains the following professional profiles:
- Profile: Computational Social Scientist
Functions:
- design and implement data collection on social phenomena (both offline and online);
- analyse these data (or supervise and coordinate their analysis);
- interpret and synthesize the results of these analyses to describe complex social phenomena, map behavioral, attitudinal, or market trends, test theories about the causes of these phenomena and trends, and provide probabilistic forecasts;
- present the results of these activities, along with the information and insights derived from them, in textual, graphical, or audiovisual formats for public or private stakeholders.
Skills: knowledge of theories and methods for quantitative research; ability to collect and critically review relevant scientific literature; proficiency in designing research and studies, including research on groups, communities, and populations, surveys, experiments, and computer simulations; data collection skills for various types of data (numerical and textual) from online and offline sources; expertise in statistical and computational analysis of data on complex social contexts using languages such as R and Python.
Outlets: companies or organizations in the private sector (e.g., social media, human resources, corporate consulting); market research agencies; local or national public administrations and government agencies; university research institutes, public or private research centers; organizations in the non-profit sector.
- Profile: Computational Analyst for Public Policy
- Functions: design and implement systematic collections of evidence and data on political phenomena, including electoral campaigns and trends, the emergence and evolution of political movements and parties, and public opinion trends; analyse these data (or supervise and coordinate their analysis); interpret and synthesise results to describe complex political phenomena, map political and electoral trends, test theories about the causes of these phenomena and trends, or predict how such phenomena may unfold in the future.
- Skills: knowledge of theories and methods of quantitative research; ability to gather and critically review relevant scientific literature; proficiency in designing research and studies, including experimental designs, randomized controlled trials, and the analysis of texts and documentary materials using quantitative and computational techniques with languages such as R and Python; expertise in predictive electoral models, political strategy analysis, campaign design, online disinformation tracking, and analysis; statistical and computational analysis of data on complex political contexts.
- Outlets: companies or organizations in the private sector (e.g., political consulting, public opinion polling, social media), local or national public administrations or government agencies, political parties and organizations, foundations and think tanks, policy evaluation agencies, non-governmental organizations, international agencies, university research institutes, public or private research centers, or non-profit organizations.