Master of Data Science

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.

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

Months of entry

October

Course content

Are you keen to find out more about the field of data science and learn the latest techniques used in the sector? Designed by data scientists for the next generation of data scientists, the Master of Data Science (MDS) develops the specialist skills you will need to manage and analyse different types of data efficiently. This advanced understanding of complex data will give you a head start in this dynamic field for your future career.

The Durham MDS provides training in contemporary data science in a supportive environment, learning from practicing researchers who are making a difference across a range of industries.

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.

The MDS 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.

You’ll begin by mastering a range of introductory modules before progressing to more advanced contemporary techniques in machine learning to expand your knowledge and understanding. We offer an extensive range of optional modules which allows you to focus on an area of interest such as text analytics and data visualization.

The MDS culminates in the research project, an in-depth investigation in which you apply the skills learned during the course to a research problem working alongside an expert in the area of application of your choice.

The course is part of a suite of courses which share some common modules, you can choose the general route or take one of the specialist pathways in:

• Bioinformatics and Biological Modelling
• Digital Humanities
• Earth and Environment
• Health
• Social Analytics
• Heritage

Course structure

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.

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.

Ethics and Bias in Data Analytics introduces contemporary debates on ethical issues and bias resulting from the application of data analytics, statistical modelling and artificial intelligence in society. You will learn about contemporary philosophical research on these issues and how to apply this research in practice. The module includes an essay about an ethical topic, completed under the guidance of a tutor.

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.

Strategic Leadership develops the skills you will need to understand organisations, their structure and culture. You will explore the leadership skills required to manage organisations and build an understanding of the emergent issues and challenges faced in fostering ethical leadership practices.

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 Mathematics for Data Science
• Introduction to Computing for Data Science
• Data Science Applications in Archaeology and Heritage
• Text Mining and Language Analytics
• Bioinformatics
• Multilevel Modelling
• Data Exploration, Visualisation and Unsupervised Learning
• Health Informatics and Clinical Intelligence
• Qualitative Approaches to Digital Humanities
• Computer Music

Information for international students

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.

Fees and funding

For further information see the course listing.