Master of Data Science (Social Analytics)
Gain the skills needed to apply new computational methods to inform policy and examine social phenomena.
1 year full-time
1 year full-time
Please note: Courses may be affected by Covid-19 and are therefore subject to change due to the ongoing impact of Covid-19. Applicants will be informed of any changes which we are required to make to course entries as a result of Covid-19.
The Master of Data Science (Social Analytics) shares a common core with the other Master of Data Science programmes. Social analytics will create a new cohort of social scientists with the necessary skills to apply new computational methods to inform policy, examine social phenomena and gain insight about the interactions between people and their social environment. It will also equip social scientists to work with social media and other new sources of data. While generic data science skills are useful for social scientists, interpreting social data comes with particular challenges. This programme includes modules about specialised methods and also the theoretical foundations to understand how to use them effectively.
Shared core modules with the suite of Data Science Master courses will ensure that you get equipped with the wider quantitative and computational skills required for your career. You will be carrying out team building activities, presenting case studies and carrying out both formative and summative assessments with students from all four faculties of Durham University, ensuring that you learn how to represent not just your own discipline but to also listen and integrate views and skills from other disciplines. An additional contribution to the academic environment will be provided by the Durham Research Methods Centre which will also help with the allocation of project topics through partnerships with local authorities, neighbouring NHS Trusts or other collaborators in the health and social care sectors.
All around us, massive amounts of increasingly complex data are being generated and collected, for instance, from mobile devices, cameras, cars, houses, offices, cities, and satellites. Business, research, government, communities, and families can use that data to make informed and rational decisions that lead to better outcomes. It is impossible for any one individual or group of individuals to keep on top of all the relevant data: there is simply far too much. Data science enables us to analyse large amounts of data effectively and efficiently and as a result has become one of the fastest growing career areas.
Previously, data science was the province of experts in maths and computer science, but the advent of new techniques and increases in computing power mean that it is now viable for non-experts to learn how to access, clean, analyse, and visualize complex data. There is thus a growing opportunity for those already in possession of knowledge about a particular subject or discipline, and who are therefore able to grasp the full meaning and significance of data in their area, to be able to undertake data analysis intelligently themselves. The combination of primary domain knowledge with an expertise in extracting relevant information from data will give those with this ‘double-threat’ a significant employment advantage.
The Master of Data Science suite of programmes is a conversion course with a hard-core of data science, intended to provide Masters-level education rich in the substance of data science for students who hold a first degree that is not highly quantitative, including those in social sciences, the arts and humanities. Introductory modules are designed to bring students with non-technical degrees up to speed with the background necessary for data science. This is done on a need-to-know basis, focusing on understanding in practice rather than abstract theory. Core modules then introduce students to the full range of data science methods, building from elementary techniques to advanced modern methods such as neural networks and deep learning. Optional modules allow students to focus on an area of interest.
The programme provides training in relevant areas of contemporary data science in a supportive research-led interdisciplinary learning environment. The broad aims are:
The programme is designed around a pedagogical framework which reflects the core categories of the data science discipline.
A number of subjects can be identified and defined within each application domain. Whilst a Masters programme cannot incorporate all subjects, a selection of subjects representative of each domain ensures that the programme incorporates the necessary breadth and depth of material to ensure a skilled graduate.
The programme allows for progressive deepening in the students’ knowledge and understanding, culminating in the research project which is an in-depth investigation of a specific topic or issue.
The global dimension is reinforced through the use of international examples and case studies where appropriate.
The Master of Data Science (Social Analytics) programme is comprised of the following core modules:
The Master of Data Science suite of programmes is research-oriented. Data Science is a driving force behind many subject specialisations today and aspects are delivered within the context of an active and varied research culture as is demonstrated via the associated academics and researchers within the Institute for Data Science.
Students are also encouraged, through a range of modules, to develop research methods, skills and ethics reflecting the wide range of methods used by the research active staff. Research methodologies are actively taught through many other modules and assessments. They are also developed through innovative teaching practices such as simulations. Overall students are encouraged and guided to be ‘research minded’ in all modules, and to develop these critical skills for the future.
All modules taught on this programme are underpinned by research, and embed elements of research training both in the delivery and in the assessment.
The Master of Data Science suite of programmes uses a wide range of learning and teaching methods:
The project is a major research project, conducted and written up as an independent piece of work with support from the student’s appointed supervisor.
Student academic support and guidance is provided through the members of the Management Board, module coordinators, and individual lecturers. This support may take the form of face-to-face contact, telephone, e-mail, or other online contact, as appropriate.
Students also have an appointed Academic Advisor who is able to guide and inform them in their academic development and choice of optional modules.
Information, requirements and expectations regarding the programme overall are provided in the Programme Handbook, which is issued to all students at the beginning of the year and is available on Blackboard Ultra afterwards. This is supplemented information on module aims/learning outcomes, content, key skills, formative and summative assessments and recommended reading.
Academic support to students is initially provided through an induction programme which provides an introduction to the University, the contributing departments, the programme, and key members of staff.
A UK first or upper second class honours degree or equivalent. Applicants with a first degree (or equivalent experience) involving significant content in Mathematics or Computer Science will be considered on a case-by-case basis.
|Home students||£11,600 per year|
|EU students||£26,900 per year|
|Island students||£11,600 per year|
|International students||£26,900 per year|
The tuition fees shown are for one complete academic year of full time study, are set according to the academic year of entry, and remain the same throughout the duration of the programme for that cohort (unless otherwise stated).
Please also check costs for colleges and accommodation.
We are committed to supporting the best students irrespective of financial circumstances and are delighted to offer a range of funding opportunities.Find out more about Scholarships and Bursaries
Natural Sciences is the Faculty of Science “Department” that facilitates multidisciplinary and interdisciplinary degrees.
All around us, massive amounts of increasingly complex data are being generated and collected and business, research, government, communities, and families can use that data to make informed andrational decisions that lead to better outcomes. Data science enables us to analyse large amounts of data effectively and efficiently and as a result has become one of the fastest growing career areas.
For more information see our department pages.
The Master of Data Sciences degree programmes combines material from across departments. The email contact is firstname.lastname@example.org