University College London (UCL)
Social Research Methods with Data Science MSc
London, United Kingdom
MSc
DURATION
1 year
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
EARLIEST START DATE
Sep 2026
TUITION FEES
STUDY FORMAT
On-Campus
This MSc program combines social research methods with data science techniques, giving students a solid grounding in understanding social phenomena through data-driven approaches. It covers core skills such as qualitative and quantitative research methods, alongside data analysis, programming, and statistics. The course is designed to prepare students to work with complex data sets and develop solutions for real-world social issues, blending traditional research skills with modern technological methods.
The program emphasizes practical learning, with opportunities to apply skills through projects and collaborations with external organizations. Students gain experience in using software tools and programming languages relevant to data science, helping them analyze social data effectively. The course caters to those interested in careers in research, policy, or analytics, providing a well-rounded foundation to interpret and present social data confidently. Throughout, the focus is on developing both technical abilities and critical thinking needed for social research in a data-rich environment.
UCL Scholarships
There are a number of scholarships available to postgraduate students, including our UCL Masters Bursary for UK students and our UCL Global Masters Scholarship for international students. You can click the link below to search via the scholarships finder for awards that you might be eligible for. Your academic department will also be able to provide you with more information about funding.
External Scholarships
Online aggregators like Postgraduate Studentships, Scholarship Search, Postgraduate Funding and International Financial Aid and College Scholarship Search contain information on a variety of external schemes.
If you have specific circumstances or ethnic or religious background it is worth searching for scholarships/bursaries/grants that relate to those things. Some schemes are very specific.
Funding for disabled students
Master's students who have a disability may be able to get extra funding for additional costs they incur to study.
Teaching and learning
The programme is delivered through a combination of lectures, seminars, practical sessions, tutorials and research supervision, and is taught by scholars who have carried out research in the field. Students are expected to take part in both guided and self-guided personal work. Lectures are often mirrored by a practical workshop seminar in a computer lab where students will put the analytical techniques introduced that week to use.
Most modules are offered as campus-based and fully online courses, with both versions of the module running in parallel. For distance-learning students, all lectures, activities and exchanges between students and tutors take place within Moodle (UCL's digital learning environment) and integrated platforms such as Zoom. In place of the face-to-face group seminars held on campus, students taking modules at a distance participate in various e-learning activities, facilitated by the tutor leading this group.
For Student visa holders, all study that is part of your course is expected to take place on the university’s premises, with Tier 4 conditions preventing selection of modules taught entirely through online study.
Assessment is carried out through a blend of formative and summative assessment methods. Module assessments on the programme vary, and may include coursework (for example, essays and written assignments), presentations, or a form of examination. You may be expected to complete both individual and group assessments. UCL’s module catalogue details individual module assessments, but please note these may be subject to change on an annual basis.
On average, it is expected that a student spends 150 hours studying for each 15-credit module. This includes teaching time, private study and coursework. The 60-credit dissertation module requires a notional learning time of about 600 hours.
Outside of lectures, seminars, workshops and tutorials, full-time students typically study the equivalent of a full-time job, using their remaining time for self-directed study and completing coursework assignments. Part-time and modular/flexible students will need one day per week for each 15-credit module, plus additional time to prepare for assessments.
Modules are taught over 10 weeks each term. For campus-based students, this is usually in the form of either a one-hour lecture followed by a one-hour seminar or workshop, or a two-hour practical workshop. Distance learners have access to the same information delivered to students studying on campus through a range of online teaching tools.
For full-time students studying on campus, typical contact hours are around 10 hours per week. In terms one and two, full-time students can typically expect between 8 and 12 contact hours per teaching week through a mixture of lectures, seminars, workshops and tutorials. In term three and the summer period, students will be completing the dissertation research, and keeping regular contact with their supervisors.
For distance-learning students, most learning activities are self-paced and asynchronous. Online discussion boards are used to help foster a sense of community, and to allow you to keep in touch with peers and academics throughout your studies. There will be opportunities for weekly one-to-one contact with your tutors. Live sessions can also be arranged where time zones permit.
Modules
Full-time
The Social Research Methods with Data Science MSc consists of four modules in quantitative methods (60 credits); four further research methods modules (60 credits); and a dissertation using quantitative methods (60 credits).
Students are expected to choose data science modules for at least half of their taught credits. The remaining credits can be chosen from additional modules in data science, qualitative research methods, and evidence synthesis methods.
The first term of the programme introduces a broad range of quantitative methodologies, ranging from data manipulation to advanced regression techniques. Modules on qualitative analysis and evidence synthesis are also on offer.
The second term allows you to develop your research interests with a range of advanced optional modules for you to choose both from areas in social data science that may include impact evaluation, longitudinal data and analysis, advanced quantitative methods, data management, and from areas based on qualitative methods such as ethnography, thematic/narrative/discourse analysis, advanced methods, applications of systematic reviews and digital mixed methods.
You will begin work on the dissertation in term one. This will be your own piece of research based on quantitative analysis methodologies.
Part-time
The Social Research Methods with Data Science MSc consists of four modules in quantitative methods (60 credits); four further modules in quantitative, qualitative, or evidence synthesis methods (60 credits); and a dissertation using quantitative research methods (60 credits).
Part-time students will complete the programme over two academic years. Up to six 15-credit modules can be taken in the first year, with the remainder taken in the second year.
During the first year of the part-time programme, you will complete at least one data science module each term, while the remaining credits will be at the choice of the student. The same pattern will apply in the second year, with the addition of a dissertation using quantitative methods.
Dissertation teaching begins in term one of the second year and includes workshops and individual supervision.
Flexible
Modular/flexible students have between two and five years in which to complete the programme, with the dissertation taken in the final year of study. You do not have to take modules every year.
The modules are taken in generally the same order as students on the full-time or the part-time routes. Following approval by the Programme Leader, module order can be varied.
Compulsory modules
- Dissertation (MSc Social Research Methods)
Optional modules
- Longitudinal Data and Analysis
- Data Science using International Data
- Advanced Qualitative Methods
- Ethnography
- Foundations of Qualitative Methods
- Intersectionality and Critical Qualitative Research
- Inclusive Research: Theory for Policy and Practice
- Systematic Reviews for Policy: Taking a Complexity Perspective
- Digital Technologies for Research Evidence Synthesis
- Approaches to Systematic Review Synthesis
- Advanced Computational Techniques for Data Science
- Advanced Social Data Science
- Foundations of Social Data Science
- Understanding Data for the Social Sciences
- Impact Evaluation Methods
Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change.
Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Architectural Computation. Upon successful completion of 120 credits, you will be awarded a PG Dip in Architectural Computation.
Fieldwork
Students may choose to organise and undertake fieldwork in relation to their research for their dissertation, but this is not a requirement. If undertaken, fieldwork must be self-funded.
Accessibility
Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information can also be obtained from the UCL Student Support and Wellbeing Services team.
What this course will give you
Social Research Methods with Data Science MSc students join the UCL Social Research Institute: a research-intensive department with world-leading experts in data science, qualitative methods, and systematic reviews - as well as a broad range of social science subjects.
Our department specialises in applying research methods to inform policy in areas such as education, health, labour markets, human development, and child/adult wellbeing.
The department’s staff has a broad range of interests, including expertise in economics, sociology, psychology, social statistics, survey methods and data collection, mixed-methods research, and policy evaluation techniques.
You will become part of a lively community of staff, PhD, MSc, and undergraduate students involved in seminars, workshops, and reading groups in addition to formal teaching.
The foundation of your career
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.
Employability
Our graduates in social sciences research methods are currently working as:
- University and college lecturers and researchers
- Civil servants in analysis and policy evaluation teams
- Third-sector employees, providing detailed analysis and evaluation of charity and NGO projects
- Teachers
- Journalists, writing on topics ranging from policy impact to social issues such as health, crime, inequality, justice
- Social researchers in think tanks and public bodies
- Market researchers, studying consumer behaviour and market trends
Networking
Our students come from a range of backgrounds from all over the world, providing great networking opportunities within the programme. Students encounter academics, researchers, alumni, and visiting speakers at seminars, lecture series, career events, workshops, and other department and student organised events. Students are kept up to date with opportunities to participate in events and apply for internships or jobs.