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Durham University: Master of Data Science (Digital Humanities)
| Institution | Durham University View institution profile |
|---|---|
| Department | Natural Sciences |
| Web | durham.ac.uk |
| Telephone | 0191 334 1000 |
| Study type | Taught |
Master of Science - MSc (PG)
Summary
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 environment. This has led to a significant increase in demand for skilled data scientists, and this demand is predicted to further grow.
Drawing on this, we have created the Master of Data Science (Digital Humanities), a conversion course that opens up a future in data science even if your first degree is in a non-quantitative subject such as 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 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. Optional modules allow you to focus on an area of interest.
The MDS culminates in the research project, an in-depth investigation into an area of specific interest in which you apply the skills you’ve learned during the course to a research problem in a humanities domain of your choice.
**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 this knowledge to practical problems in data science, including your own research project.
**Digital Humanities: Practice and Theory** introduces you to contemporary debates on the future of the humanities in an increasingly digital world. You will learn about the most important technical tools for representing and manipulating cultural artefacts in digital form, and how to apply cutting-edge theoretical frameworks and technical tools to practical problems in Digital Humanities.
**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.
**Machine Learning** introduces the essential knowledge and skills required in machine learning for data science using the R statistical language. You will develop an understanding of the theory, computation and application of topics such as modern regression methods, decision-based machine-learning techniques, support vector machines, and neural networks.
| Level | RQF Level 7 |
|---|---|
| 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 Arts and Humanities are strongly encouraged to apply. Evidence of competence in written and spoken English if the applicant’s first language is not English: |
| Location | Durham City Palatine Centre Durham DH1 3HP |
Fees
| England | 14500 GBP for Year 1 |
|---|---|
| Northern Ireland | 14500 GBP for Year 1 |
| Scotland | 14500 GBP for Year 1 |
| Wales | 14500 GBP for Year 1 |
| Channel Islands | 14500 GBP for Year 1 |
| EU | 34000 GBP for Year 1 |
| International | 34000 GBP for Year 1 |
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.
| Level | RQF Level 7 |
|---|---|
| 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) |
| Location | Durham City Palatine Centre Durham DH1 3HP |
Fees
| England | 13500 GBP for Year 1 |
|---|---|
| Northern Ireland | 13500 GBP for Year 1 |
| Scotland | 13500 GBP for Year 1 |
| Wales | 13500 GBP for Year 1 |
| Channel Islands | 13500 GBP for Year 1 |
| EU | 31500 GBP for Year 1 |
| International | 31500 GBP for Year 1 |
| Republic of Ireland | 31500 GBP for Year 1 |
Durham University
- World top 100 University: 78th in the QS World University Rankings 2024
- UK top 10 University: 7th in the Times and Sunday Times Good University Guide 2024 and Guardian University Guide 2024
- 8th in the Complete University Guide
- 53rd in the QS World University rankings for Sustainability 2023
- 50th in the world in the category of Employer Reputation. QS World University Rankings 2024
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