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Course summary

Are you looking to follow a career in data, or are you passionate about progressing in your chosen area of expertise? With data playing an increasingly significant role, and impacting all areas of our lives, expertise in data science is becoming ever more important. The Master of Data Science is for students holding a degree that is not highly quantitative in nature. It provides the opportunity to study a programme rich in the substance of data science. This course with a hard-core of data science will provide you with a Masters-level education focused on data science. Whether you have a background in social sciences, arts and humanities or any other discipline without data science at its core, this programme provides a range of options for you. Programme choices Master of Data Science (Digital Humanities) Master of Data Science (Social Analytics) Master of Data Science (Health) Master of Data Science (Earth and Environment) Master of Data Science (Bioinformatics and Biological Modelling) Why Master of Data Science? 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. Businesses, researchers, government, communities, and families can use that data to make informed and rational decisions that lead to better outcomes. It is impossible for anyone 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. The advent of new techniques and increases in computing power means that data science is now much more accessible to all. Our programme will support you to learn how to access, clean, analyse, and visualize complex data. This learning, along with your expertise in your degree subject or discipline, and experience will enable you to grasp the full meaning and significance of data in your area, undertaking data analysis intelligently and providing a significant employment advantage. The programme Whether you choose the core Master of Data Science or one of our more specific programmes relating to your knowledge, discipline expertise or area interest, you will find all introductory modules are designed to bring students 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 you 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 you to focus on an area of interest. The course provides training in relevant areas of contemporary data science in a supportive research-led interdisciplinary learning environment. The broad aims are: • To provide you with an advanced understanding of data science, with the skills needed to apply this to your work • To develop your skills to enable you to critically review, interpret and apply relevant data science knowledge to practical situations • To develop the ability to conduct research into data science issues that requires familiarity with a range of data, research sources and appropriate methodologies and ethical issues. A number of subjects can be identified and defined within each application domain. Whilst a Masters cannot incorporate all subjects, a selection of subjects representative of each domain ensures that the course incorporates the necessary breadth and depth of material to ensure a skilled graduate. The Masters allows for progressive deepening in your 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.


Core modules The Master of Data Science is comprised of the following core modules: Introduction to Computer Science (optional under certain conditions) Introduction to Statistics for Data Science Ethics and Bias in Data Analytics Machine Learning Programming for Data Science Strategic Leadership Introduction to Mathematics for Data Science (optional under certain conditions) Research Project Examples of optional modules: Text Mining and Language Analytics Data Exploration, Visualization, and Unsupervised Learning Multilevel Modelling

Assessment method

The Master of Data Science 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 degree are underpinned by research, and embed elements of research training both in the delivery and in the assessment. The Master of Data Science uses a wide range of learning and teaching methods: Lectures Seminars Workshops Computer/practical classes Independent study, research and analysis Structured reading Case studies Data Science Project Supervisions Group and individual oral presentations 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.

How to apply

International applicants

If you are an international student who does not meet the requirements for direct entry to this degree, you may be eligible to take a pre-Masters pathway programme at the Durham University International Study Centre.

Entry requirements

A UK first or upper second class honours degree or equivalent in ANY degree that is not highly quantitative, including those in social sciences, the arts and humanities 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

English language requirements

Durham University welcomes applications from all students irrespective of background. We encourage the recruitment of academically well-qualified and highly motivated students, who are non-native speakers of English, whose full potential can be realised with a limited amount of English Language training either prior to entry or through pre-sessional and/or in-sessional courses. It is the normal expectation that candidates for admission should be able to demonstrate satisfactory English proficiency before the start of a programme of study, whether via the submission of an appropriate English language qualification or by attendance on an appropriate pre-sessional course. Acceptable evidence and levels required can be viewed by following the link provided.

English language requirements

Fees and funding

Tuition fees

England £13500 Year 1
Northern Ireland £13500 Year 1
Scotland £13500 Year 1
Wales £13500 Year 1
Channel Islands £13500 Year 1
EU £31500 Year 1
International £31500 Year 1
Republic of Ireland £31500 Year 1

Additional fee information

The tuition fees shown are for one complete academic year of 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).

Sponsorship information

For further information see the course listing.

Master of Data Science at Durham University - UCAS