Master of Data Science

Program Overview

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Course Overview

The Master of Data Science (MDS) is a conversion course that develops the specialist skills needed to manage and analyze different types of data efficiently. This advanced understanding of complex data will give students a head start in this dynamic field.

Start Dates

• September 2025

Degree Type

• MDS

Course Length

• 1 year full-time

Location

• Durham City

Programme Code

• G5K823

Course Structure

Year 1 Modules

Core Modules:

• Data Science Research Project: A substantial piece of research into an unfamiliar area of data science, or in the student's subject specialisation area with a focus on data science.
• Critical Perspectives in Data Science: Develops understanding of the production, analysis, and use of quantified data, and how to analyze these practices anthropologically.
• Programming for Data Science: Uses the popular Python software packages used in a wide range of industry settings.
• Ethics and Bias in Data Analytics: Introduces contemporary debates on ethical issues and bias resulting from the application of data analytics, statistical modeling, and artificial intelligence in society.
• Machine Learning: Introduces the essential knowledge and skills required in machine learning for data science using the R statistical language.
• Strategic Leadership: Develops the skills needed to understand organizations, their structure, and culture.

Optional Modules:

• 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 Modeling
• Data Exploration, Visualization, and Unsupervised Learning
• Health Informatics and Clinical Intelligence
• Qualitative Approaches to Digital Humanities
• Computer Music

Learning

This interdisciplinary course incorporates a wide range of learning and teaching methods, including lectures, seminars, workshops, and computer/practical classes. The taught elements are further reinforced through independent study, research, and analysis, case studies, and structured reading.

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 comes together with a major research project, which is conducted and written up as an independent piece of work with support from the appointed supervisor.

Entry Requirements

• A UK first or upper second-class honors 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 IELTS requirement is 6.5 overall, with no component under 6.0
  • Minimum TOEFL requirement is 92 overall, with no component under 23

Alternative Qualifications

• Other UK qualifications
• EU qualifications
• International qualifications

Fees and Funding

Full-Time Fees

• Home students: £14,500 per year
• EU students: £34,000 per year
• Island students: £14,500 per year
• International students: £34,000 per year

Career Opportunities

The skills and knowledge that constitute a Master's qualification in Data Science are widely sought by employers around the globe. In today's data-driven society, the ability to capture, analyze, and communicate information and trends from the data generated by business, governments, and their agencies, communities, and organizations is highly prized.

Department Information

The Master of Data Science is part of a suite of courses that share some common modules. The course is offered as a conversion course for those who hold a first degree that doesn’t have a strong component in data science. Seven qualifications are available, including the broad Master of Data Science and specialist routes in Bioinformatics and Biological Modeling, Digital Humanities, Earth and Environment, Health, Social Analytics, and Heritage.

Facilities

Data Science is a conversion course that incorporates content from many departments across the University. This provides access to a selection of related state-of-the-art facilities from across the University, in particular, Computer Science and Mathematics. Facilities will depend on the subject specialism but include laboratories, libraries, project spaces, lecture theaters, study and networking spaces, as well as shared social spaces. Most departments are close to the historic center of Durham, which is a UNESCO World Heritage site.

Program Outline

This program provides an advanced understanding of complex data, giving graduates a competitive edge in this dynamic field.

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Objectives:

• Develop specialized skills in data management and analysis.
• Gain a thorough understanding of contemporary data science techniques.
• Prepare graduates for a successful career in data science.

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Program Description:

The MDS curriculum combines introductory and advanced modules, allowing students to build a strong foundation in data science while exploring specialized areas of interest. The program culminates in a research project where students apply their acquired skills to investigate a specific topic in data science.

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Outline:

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Program Content:

The MDS program covers a wide range of topics, including:

• Data manipulation and analysis
• Machine learning
• Statistical modeling
• Data visualization
• Data ethics
• Programming for data science
• Research methods

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Program Structure:

The MDS program is a one-year full-time course. It consists of a combination of core and optional modules.

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Individual Modules:

• Data Science Research Project: An in-depth investigation into a specific area of data science, focusing on research, analysis, and report writing.
• Critical Perspectives in Data Science: Develops an understanding of data production, analysis, and ethical considerations in data science practices.
• Programming for Data Science: Utilizes Python software packages for data manipulation, analysis, and visualization.
• Ethics and Bias in Data Analytics: Examines contemporary debates on ethical issues and biases in data analytics and artificial intelligence.
• Machine Learning: Introduces essential knowledge and skills in machine learning for data science, covering topics like regression methods, decision-based learning, support vector machines, neural networks, and deep learning.
• Strategic Leadership: Develops the skills to understand organizations, their structures, and cultures, exploring leadership skills and emergent challenges in fostering ethical leadership practices.

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Additional Modules:

Depending on prior qualifications and experience, students may choose from various optional modules, including:

• 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, Visualization and Unsupervised Learning
• Health Informatics and Clinical Intelligence
• Qualitative Approaches to Digital Humanities
• Computer Music

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Assessment:

The MDS program utilizes a多元化评估方法,包括:

• Essays
• Online assessments
• Reports
• Presentations (individual and group)
• A major research project

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Teaching:

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Teaching Methods:

The MDS program employs a variety of teaching methods, including:

• Lectures
• Seminars
• Workshops
• Computer/practical classes
• Independent study
• Research and analysis
• Case studies
• Structured reading

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Faculty:

The MDS program is taught by research-active staff who are experts in their respective fields.

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Unique Teaching Approach:

The program emphasizes research-Informed teaching, integrating elements of research training into both delivery and assessment. Students are encouraged to develop research methods, skills, and ethics, reflecting the methods used by the research-active staff.

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Careers:

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Career Opportunities:

Graduates of the MDS program are well-equipped for a range of careers in data science, including:

• Data analyst
• Data scientist
• Research scientist
• Statistician
• Machine learning engineer
• Data visualization specialist
• Business intelligence analyst

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Career Support:

Durham University provides career support services to help students find employment opportunities and develop their careers.

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Other:

• The MDS program is open to students with first or upper second class honors degrees in any subject, including those in social sciences, the arts and humanities, business, and sciences.
• Evidence of English language proficiency is required for non-native English speakers.
• The program is part of a suite of courses that share some common modules.
Students can choose the general route or take one of the specialist pathways in Bioinformatics and Biological Modelling, Digital Humanities, Earth and Environment, Health, or Social Analytics.

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Conclusion:

The Master of Data Science at Durham University is a comprehensive program that provides students with the knowledge, skills, and experience needed to succeed in the field of data science. The program's strong emphasis on research, combined with its diverse teaching methods and career support services, makes it an ideal choice for individuals seeking to advance their careers in this rapidly growing field.

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Full Time Fees

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Tuition fees

Home students £13,500 per year EU students £31,500 per year Island students £13,500 per year International students £31,500 per year The tuition fees shown are for one complete academic year of full time 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).