The Master of Data Science with AI Applications at Durham University is a career-focused conversion course for graduates from diverse backgrounds, equipping you with technical, analytical, and AI skills through hands-on learning preparing you for roles in finance, healthcare, tech, public policy, and beyond.
The Master of Data Science with AI Applications is designed to equip aspiring professionals with the latest tools and techniques used in the sector empowering you to manage, analyse, and extract insights from complex data, and preparing you for high-impact roles in AI-driven fields such as tech, healthcare, finance, and beyond.
The Durham MDS with AI Applications 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 AI technologies have made the field of data science more accessible than ever, creating new opportunities to gain insight into the interactions between people, AI systems and their environment. This has led to a significant increase in demand for skilled data scientists with specialisation in AI.
The MDS programme opens up a future in data driven careers even if your first degree is in an unrelated subject (including the social sciences, the arts and humanities). The programme 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 programme culminates with a 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.
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
Environmental Data Science
Health
Social Analytics
Heritage
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.
Course structure
Year 1 modules
Core modules:
The Data Science Research Project
is a substantial piece of self directed 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 and AI
develops your understanding of the production, analysis and use of quantified data, and how to analyse these practices anthropologically utilising AI applications. 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 of Artificial Intelligence and Data Science
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.
AI and HCI Interactions
explore how humans and intelligent systems interact in the real world. This module introduces the theories, methods, and tools for designing and evaluating interactive AI systems through a human-centred lens, examining how design choices influence user experience, trust, and ethical outcomes. You'll gain the skills to create AI technologies that are not only intelligent but also intuitive, responsible, and socially aware.
Optional modules:
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 ScienceText Mining and Language Analytics
Multilevel Modelling
Data Exploration, Visualisation and Unsupervised Learning
This interdisciplinary course is made up of modules that span across the University. It incorporates a wide range of learning and teaching methods , these include lectures, seminars, workshops and computer/practical classes. The taught elements are further reinforced through independent study, research and analysis, case studies and structured reading.
All modules are underpinned by research and embed elements of research training in both delivery and assessment. Throughout the course you will be encouraged to develop research methods, skills and ethics reflecting the methods used by the research-active staff. Overall, you will be encouraged and guided to be ‘research minded’ in all modules, and to develop these critical skills for use in future work or research.
Assessment
The Master of Data Science is assessed via a combination of essays, online assessments, reports and presentations – both individual and in small groups.
The course culminates with a major research project, which is conducted and written up as a self-directed piece of work with support from your appointed supervisor.
Entry requirements
We require a 2:1 Bachelor (Honours) degree or international equivalent in any degree subject.
Applicants with a strong data science or mathematical background may wish to consider our MSc Scientific Computing and Data Analysis programmes.
International students who do not meet direct entry requirements for this degree might have the option to complete an International Foundation Year.
Home students who do not meet our direct entry requirements, may be eligible for our Foundation Programme which offers multidisciplinary programmes to prepare you for a range of specified degree programmes.
The fees for this academic year have not been confirmed yet.
The tuition fees shown are for one complete academic year of study and are set according to the academic year of entry. Fees will be subject to an annual inflationary increase and are expected to rise throughout the programme of study. The fee listed above is for the first year of the course only.
In today’s data-driven world, the ability to capture, analyse, and communicate insights from complex information is one of the most sought-after skills by employers globally.
Graduates are equipped for exciting and meaningful careers across a wide range of sectors from science, health, and the environment to the humanities and social policy where data is driving innovation and transforming how we live and work. Whether you're influencing public health strategies, advancing climate research, or unlocking cultural insights, your data science expertise will open doors to impactful opportunities.
Department information
Natural Sciences
Our Master of Data Science programmes give you the tools to capture, analyse, and unlock insights from the vast streams of data shaping our world. These interdisciplinary degrees empower smarter decision-making across sectors from health and environment to culture and society.
The Master of Data Science programmes at Durham University equip you with the skills to capture, process, and analyse the vast and complex data shaping every aspect of modern life. From healthcare and environmental science to social policy and cultural heritage, data science is transforming how decisions are made and problems are solved.
The suite of programmes are designed as conversion degrees, ideal for students from non-data science backgrounds who want to transition into this high-impact field. You'll gain a strong foundation in data science while exploring its applications across a range of disciplines.
Choose from seven pathways tailored to your interests and career goals: the Master of Data Science or Master of Data Science with AI Applications, or specialist routes in Bioinformatics and Biological Modelling, Digital Humanities, Earth and Environment, Health, Social Analytics, and Heritage.
As a student, you’ll benefit from Durham’s interdisciplinary approach and the expertise of the Institute for Data Science, a hub for innovation that supports research and teaching across the University. Join a vibrant academic community working to transform nature, society, and culture through data.
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