Master of Data Science (Digital Humanities) at Durham University - UCAS

Durham University

Degree level: Postgraduate

Master of Data Science (Digital Humanities) (Taught)

Course options

Course summary

The Master of Data Science (Digital Humanities) 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 in the Humanities. 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. Introductory modules are designed to bring students who are complete beginners and will require no prior knowledge of mathematics or programming 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. Data Science core modules will include an introduction to mathematics for Data Science, statistical modelling (in R), computer programming (in Python), machine learning, AI and neural networks. In addition to that Data Science core, you will also take a module in Digital Humanities which will explore the application of quantitative and computational methods to cultural data: languages, literary, philosophical and theological texts, historical data, artifacts and material culture, visual art, video and music. Alternatively, you may take a traditional MA module in your area of interest (subject to departmental approval and timetabling). Optional modules allow students to focus on an area of interest. The degree provides training in relevant areas of contemporary data science in a supportive research-led interdisciplinary learning environment. A number of subjects can be identified and defined within each application domain. Whilst a Masters degree 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 where you will apply the techniques you have learned from your Data Science modules to a research problem in a Humanities domain of your choosing. The global dimension is reinforced through the use of international examples and case studies where appropriate.

Modules

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

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 programme are underpinned by research, and embed elements of research training both in the delivery and in the assessment.


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

https://www.durham.ac.uk/study/international/entry-requirements/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 (Digital Humanities) at Durham University - UCAS