Social Data Science University of Oxford

Overview

The MSc in Social Data Science at the University of Oxford is a rigorous and multidisciplinary course aimed at students interested in applying computational methods to significant social and political questions. As the landscape of big data and artificial intelligence (AI) continues to evolve, there is an increasing demand for professionals who can leverage these tools while considering their social implications. This programme not only focuses on the application of machine learning and multivariate statistics but also emphasises the ethical, legal, and governance aspects of data usage in society.

Administered by the Oxford Internet Institute (OII), the course draws on expertise from various departments, including Engineering Science, Mathematics, Linguistics, Statistics, and Sociology. This collaborative approach enhances the learning experience, providing students with diverse perspectives on the complex issues surrounding data science. The programme is structured to accommodate students from various academic backgrounds, although a familiarity with programming and a strong foundation in social sciences are advantageous.

The University of Oxford is renowned for its academic excellence and innovative research. The OII stands out as a leading department dedicated to understanding the societal impacts of the internet and digital technologies. Students benefit from a vibrant academic community, access to world-class resources, and opportunities to engage with leading experts in the field. The department's commitment to interdisciplinary collaboration ensures that students are well-prepared to tackle the complex challenges of the digital age.

For the academic year 2025-26, the tuition fees for the MSc in Social Data Science are as follows:

• Home: £27,600 per year
• International: £36,250 per year

Visit the Fees and Funding section for a breakdown in your local currency.

The course comprises a blend of compulsory intensive and foundation courses, along with elective modules. Key components include:

• Compulsory Intensive Course: Data Science and Machine Learning - covering Python programming fundamentals, computational complexity, and introductory machine learning.
• Compulsory Foundation Courses:
  • Foundations and Frontiers of Social Data Science - exploring fundamental questions in the field.
  • Applied Analytical Statistics - focusing on techniques for analysing quantitative data.
  • Research Design for Social Data Science - introducing methodological aspects of social science research.
• Option Modules: Students can choose from various subjects, including Applied Machine Learning, Digital Era Government and Politics, and Social Network Analysis.

Students are expected to dedicate approximately 40 hours per week to their studies, with a structured timetable that includes lectures, tutorials, and practical exercises. The intensive nature of the course does not permit part-time study options, although students may consider transitioning to a part-time DPhil programme post-MSc.

Graduates of the MSc in Social Data Science are well-equipped for diverse career paths in various sectors, including technology, government, and non-profit organisations. Alumni have found positions at leading companies such as Google and Meta, as well as dynamic start-ups like Spotify and TikTok. Many graduates pursue further academic research, enrolling in prestigious doctoral programmes at institutions like Oxford and Cambridge, thereby enhancing their expertise and career prospects.