Gain advanced data science and AI skills that can be used to inform policy and business decisions. This course will equip you with social data knowledge and skills that can be used to change people’s lives for the better.
From personalised medicine to smart cities and sustainable solutions, data science is building a better world. At the same time, developments in technology have made the field of data science more accessible than ever, creating new opportunities to gain insight into the interactions between people and their social environment. With companies and organisations of all types harnessing this technology to advance knowledge and aid policy and business decisions, there has been a significant increase in demand for skilled data scientists.
Drawing on this, we have created the Master of Data Science (Social Analytics), a conversion course that opens up a future in data science even if your first degree is in a non-quantitative subject (including the social sciences, the arts and humanities). The course equips you with the skills to process and analyse data, communicate your findings to a wide audience whilst applying this knowledge to practical situations.
The MDS provides training in contemporary data science, learning from practicing researchers who are making a difference across a range of industries. Shared core modules across the suite of MDS courses build wider skills in statistical and machine learning, while subject-specific modules integrate data science with social science, equipping you with the skills to design and carry out social data science research and communicate it to optimise impact across a variety of settings.
The course begins with a range of introductory modules before progressing to more advanced contemporary techniques such as statistical modelling (in R), computer programming (in Python), machine learning, AI and neural networks. Social analytics modules provide insight into the specialised methods needed for social data as well as the theoretical foundations to understand how to use them effectively.
The MDS culminates in the research project, an in-depth investigation into an area of specific interest in which you apply the skills learned during the course to a research problem in a social science domain of your choice. The Durham Research Methods Centre can help with the allocation of project topics through local authorities, NHS Trusts and the wider health and social care sector.
Course structure
Year 1 modules
Core modules:
The Data Science Research Project
is a substantial piece of research into an unfamiliar area of data science, or in your subject specialisation area with a focus on data science. The project can be practical, theoretical or both, and is designed to develop your research, analysis and report-writing skills.
Critical Perspectives in Data Science
develops your understanding of the production, analysis and use of quantified data, and how to analyse these practices anthropologically. You will learn to think ethically and contextually about quantified data, and how to apply these tools to practical problems in data science, including your own research project.
Social Science: Questions, Concepts, Theories and Methods
illustrates the key differences between the field of social science and other disciplines. It facilitates understanding of different types of data; uses practical examples from the social sciences to teach research design and measurement methods; and introduces state of the art applications of computational methods in social science.
Programming for Data Science
uses the popular Python software packages used in a wide range of industry settings. You will learn how to gather, manipulate and process real-world data and learn the key concepts of data analysis and data visualisation.
Introduction to Statistics for Data Science
focuses on the fundamentals of statistics you will need for data science. The module covers topics such as exploratory statistics, statistical inference; linear models; classification and clustering methods; and resampling and validation.
Year 2 modules
Optional modules:
The remainder of the course will be made up of core and option modules which will vary depending on prior qualifications and experience. These have previously included:
Introduction to Computer Science
Introduction to Mathematics for Data Science
Text Mining and Language Analytics
Data Exploration, Visualisation and Unsupervised Learning
Ethics and Bias in Data Analytics
Strategic Leadership
Machine Learning
Computational Social Science
Accreditation
Data science is one of the fastest growing professions, and with increasing quantities of complex data generated and collected daily, the demand for skilled data scientists shows no sign of slowing.
When data is analysed effectively, the findings can be used by businesses, researchers and governments as well as on a smaller scale in communities and families to make informed and rational decisions that lead to better outcomes for individuals and societies.
Students from Durham’s MDS (Social Analytics) graduate with the skills to process and analyse data to identify patterns, and interpret trends to support decision making and identify opportunities. Our graduates are highly valued by employers and progress into a diverse range of careers in areas including academia, local and national government, NGOs, market research, and in financial and professional services. Many take their data analysis skills into fields related to their undergraduate discipline while others move into more specialised roles in data engineering and data science.
This interdisciplinary course is made up of modules that span departments across the University. It incorporates a wide range of learning and teaching methods which vary according to the modules studied. These include lectures, seminars, workshops and computer/practical classes. The taught elements are further reinforced through independent study, research and analysis, case studies and structured reading.
All modules are underpinned by research and embed elements of research training in both delivery and assessment. Throughout the course you will be encouraged to develop research methods, skills and ethics reflecting the methods used by the research-active staff. Overall, you will be encouraged and guided to be ‘research minded’ in all modules, and to develop these critical skills for use in future work or research.
Assessment
The Master of Data Science (Social Analytics) is assessed via a combination of essays, online assessments, reports and presentations – both individual and in small groups.
The course culminates in a major research project, which is conducted and written up as an independent piece of work with support from your appointed supervisor.
Entry requirements
A UK first or upper second class honours degree or equivalent in ANY degree that doesn’t include a strong data science component including those in social sciences, the arts and humanities, business, and sciences. Candidates with a degree in Social and Behavioural Sciences are strongly encouraged to apply.
Evidence of competence in written and spoken English if the applicant’s first language is not English:
minimum TOEFL requirement is 102 IBT (no element under 23)
minimum IELTS score is 7.0 overall with no element under 6.0 or equivalent
The tuition fees shown are for one complete academic year of study and are set according to the academic year of entry. Fees will be subject to an annual inflationary increase and are expected to rise throughout the programme of study. The fee listed above is for the first year of the course only.
The skills and knowledge that constitute a Masters qualification in Data Science are widely sought by employers around the globe. In today’s data-driven society, the ability to capture, analyse and communicate information and trends from the data generated by business, governments and their agencies, communities and organisations is highly prized.
It follows that Data Science is a rapidly expanding career sector with opportunities for stimulating and rewarding work in many sectors including the areas of science, humanities, health, environmental and social where understanding and expertise in data is leading to transformations in the way people live and work.
Department information
Natural Sciences
Our Masters of Data Science programmes deliver the expertise to capture and analyse the huge amounts of data being generated across the world. The suite of interdisciplinary degrees unlocks key information that will ultimately result in more informed decisions being made in all areas of life.
The Masters of Data Science programmes developing expertise on the capture and processing information derived from the vast volumes of complex data being generated across the globe that affects all our lives.
A wide range of groups such as businesses, researchers, governments, communities, families and individuals can all use that data to make more informed decisions and therefore increase the chances of better outcomes for society, in fields such as health, environmental sciences, and social analytics.
In an academic context, data science has a key role in underpinning research activity around many subject specialisms. Our Master of Data Science degrees are offered as conversion courses for those who hold a first degree that doesn’t have a strong component in data science.
Seven qualifications are available including the broad Master of Data Science as well as specialist routes in Bioinformatics and Biological Modelling, Digital Humanities, Earth and Environment, Health, Social Analytics, and Heritage.
Durham University is also home to the specialist Institute for Data Science, which acts as a hub for new ideas and works to realise its vision to help transform nature, society and culture. The Institute has many years of supporting taught degrees from Departments across the University.
Data Science is a conversion course that incorporates content from many Departments across the University. This provides access to a selection of related state-of-the-art facilities from across the University, in particular Computer Science and Mathematics.
Facilities will depend on the subject specialism but include laboratories, libraries, project spaces, lecture theatres, study and networking spaces as well as shared social spaces. Most departments are close to the historic centre of Durham which is a UNESCO World Heritage site.
Apply
Find out more:
Apply for a postgraduate course (including PGCE International) via our online portal.
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