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MSc Social Research Methods with Data Science

  • DeadlineStudy Details:

    MSc 1 year full-time 2 years part-time 5 years flexible

Masters Degree Description

Social Research Methods with Data Science MSc is designed to cover cutting-edge research methods, with a focus on data science, used in collating evidence for the analysis, critique and evaluation of substantive issues in the social sciences, such as social justice, health disparities, migration, crime, gender, political identity. It can be studied on campus or online, allowing you to engage with the programme from anywhere in the world. 

Students in this degree will learn data science in-depth and can choose either this as their speciality or a mixed methods approach to their curriculum, including qualitative methods and evidence synthesis. They are encouraged to apply their understanding of methodology to critique existing research, design their own research, carry out their own analysis and communicate clearly with academic specialists and non-specialists. All students gain hands-on experience in a range of methodologies used to study issues of interest in the real world.

Entry Requirements

A minimum of an upper second-class Bachelor’s degree from a UK university or an overseas qualification of an equivalent standard, in a social science discipline.

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Fees

For fees and funding options, please visit website to find out more

Programme Funding

UCL offers a range of financial awards aimed at assisting both prospective and current students with their studies.

Student Destinations

Graduates with skills in social data science are in demand from a wide range of employers, including government departments, academic institutions, the media, finance and marketing.

Module Details

Compulsory modules

  •  Dissertation (MSc Social Research Methods)

Optional modules

  •  Advanced Quantitative Methods
  •  Introduction to Regression Analysis
  •  Data Analysis in the Real World
  •  Understanding Data for the Social Sciences
  •  Impact Evaluation Methods
  •  Longitudinal Data and Analysis
  •  Data Science using International Data
  •  Advanced Qualitative Methods
  •  Ethnography
  •  Introduction to Qualitative Methods
  •  Intersectionality and Critical Qualitative Research
  •  Research Engagement, Participation and Impact
  •  Systematic Reviews for Complex Policy Issues
  •  Digital Methods
  •  Systematic Review Design and Planning
  •  Approaches to Systematic Review Synthesis

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