This two-year, full-time master's program is delivered entirely in English and brings together students with both technical and social-science backgrounds to deepen analytical abilities and build an informed understanding of public policy. The curriculum emphasizes using data science and AI responsibly to inform decision-making, preparing students to turn complex data into practical, ethical policy interventions across public, private and non-profit sectors.
Students start by developing a solid technical foundation—courses include topics such as data structures and algorithms—while also studying the core principles of public policy. The programme is organised into eight linked modules that prioritise hands-on training and professional development, helping students strengthen skills in data science, ethical decision-making, good governance and leadership. A wide range of elective courses in data science, public policy and international affairs lets students tailor their studies and gain the analytical tools and conceptual grounding needed to pursue a Master’s thesis on a concrete problem in the broader data-science policy space.
The first year builds a rigorous technical and policy foundation. In semester one you cover core computing and policy basics — data structures and algorithms, an introduction to data science, the policy process, and economics. In semester two you deepen the quantitative toolkit with mathematics for data science, causal inference, and machine learning while also studying law and governance to understand the legal and institutional context for data-driven policies. Between the two years you are required to complete a summer internship; students seeking more extensive practical experience may instead apply for a full “Professional Year.”
In the final year you shift toward the governance, management and leadership dimensions of data and AI. Coursework addresses the challenges of governing data and artificial intelligence and develops skills in management and leadership so graduates can design, implement and oversee data-informed public policies. You also choose two electives to tailor the degree — options span advanced data science, public policy and international affairs — enabling specialization or broader interdisciplinary exposure.
Key learning outcomes include technical competence in algorithms, mathematics, causal inference and machine learning; the ability to translate data analysis into policy-relevant insights; a solid grasp of legal and governance frameworks affecting data and AI; and leadership and management capabilities required to implement and oversee data-driven initiatives in public and international settings.
Requirements (at a glance)
To be eligible, applicants must hold a completed undergraduate degree (BSc, BA or an international equivalent) and demonstrate fluency in English. International applicants should ensure their prior degree is recognized as equivalent in the admissions process and be prepared to provide evidence of English proficiency where required.
Applications are evaluated holistically across three main areas. Admissions decisions weigh academic achievement and qualifications, personal suitability and motivation, and quantitative/technical ability. Applicants should submit transcripts, a CV and motivation materials, and any documentation that demonstrates their quantitative skills (for example prior coursework, projects, competitions or research). Consult the program website for the full list of required documents and detailed admission rules.
All elements of an application are considered together; strong performance in one area can complement weaker evidence in another, but applicants are expected to meet the core prerequisites listed below.
Requirements (what the selection committee assesses)
For the complete list of required documents, deadlines and specific evidence accepted for English proficiency and degree equivalency, please refer to the program’s official admissions webpage.
Winter Semester (International)
15 January 2026
Winter Semester (EU/EEA)
15 February 2026
Graduates are prepared for data-driven roles at the intersection of technology and policy, including positions in government agencies, international organisations, think tanks, NGOs, public-sector analytics teams, policy consulting firms, and responsible AI teams within private companies. The programme's combination of technical training, policy expertise and applied internships strengthens employability in roles such as policy data scientist, AI/governance analyst, public policy advisor, and research analyst.
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