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School of Architecture, Computing and Engineering

MRes Data Science

MRes

The MRes Data Science is an advanced, research-intensive degree designed to develop innovative researchers who can push the boundaries of data science and tackle complex global challenges across industry and academia.

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The MRes Data Science is an advanced, research-intensive degree designed to develop innovative researchers who can push the boundaries of data science and tackle complex global challenges across industry and academia.

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MRes
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School of Architecture, Computing and Engineering
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Why choose this course?

The MRes Data Science is an advanced research degree that prepares students to conduct innovative research in data science. This programme emphasises original contribution to the field while developing sophisticated research capabilities essential for both academic and industry leadership positions.

The MRes Data Science positions you at the forefront of data science research and innovation. In today's rapidly evolving technological landscape, there is unprecedented demand for researchers who can advance data science capabilities and address complex challenges across various sectors.

This research-intensive programme has been crafted by leading experts to develop researchers capable of pushing the boundaries of data science technology. From healthcare diagnostics to climate change solutions, our students engage with pressing global challenges through original research.

What's unique about this course?

  • Advanced Software: Industry-standard tools including R, Python, TensorFlow and PyTorch
  • Research Excellence: Direct supervision from active data science researchers
  • Flexible Study: Two days per week across 12-week terms
  • Modern Facilities: Purpose-built data science laboratories
  • Industry Links: Partnerships with leading tech companies

What happens on the course?

The MRes Data Science focuses on intensive research training and independent investigation. The programme topics includes:

  • Deep learning architectures
  • Natural language processing
  • Data Science ethics and governance
  • Advanced research methodology
  • Academic writing and publication
  • Data analysis and interpretation
  • Research presentation skills

Placements on the course

We’ve built professional placements into every degree, every student will be guaranteed a professional placement. Our placements give you the real-world exposure and proven experience your CV needs, while building the industry networks essential for your career.

These short-term, structured experiences include:

  • Short duration: condensed work-like experience in professional environments
  • Academic integration: always linked to coursework, assessments or professional development modules
  • Project-based learning: students work on specific tasks or research with an organisation
  • Flexible format: can be in-person, remote, hybrid or virtual
  • Skill development: enhances workplace skills like communication, teamwork and problem-solving
  • Experiential learning: helping to close the gap between knowledge gained and the skills needed to succeed

Employability on the course

Our courses are designed from day one to prepare you for your future career. You will benefit from:

  • Extended induction: a period to familiarise yourself with your new university
  • Structured learning pathways: courses are crafted with a focus on preparing students for future careers
  • Hands-on project experience: projects and practical activities designed around real-world activities
  • Embedded professional development: all courses are designed with workplace skills development and professional placements as part of the course
  • Industry-informed modules: course content is kept up-to-date with industry standards through our industry links, staff's research and work in the field

 

Course Modules

Module: 7CS115
Credits: 30
Period: 1
Type: Core

This module provides students with a comprehensive introduction to the theory and applications of Data Science. Throughout the module, students will learn the theory behind different data science methods and how to apply them to real-world problems. The latest cutting-edge data science technologies and necessary knowledge acting as a stepping stone to carry out research in data science are also discussed in this module.

Module: 7CS113
Credits: 120
Period: 1
Type: Core

The Dissertation is an independent study module in which students will negotiate, plan, manage and execute a programme of research and analysis. In addition, students will develop skills in critical thinking and report writing. Students will complete a research dissertation within their computing discipline.

Module: 7CS112
Credits: 30
Period: 1
Type: Core

In order to understand and make predictions researchers need to be able to not only assess, examine and interpret data, but also be able to communicate their findings in ways that conveys empirical rigor and trustworthiness. This module will set learners on the path to scientific success by supporting the development of competencies such as the formulation of research ideas, the design of research studies that enable the collection and analysis of valid data whilst operating within the parameters of ethical principles. Students will develop their analytical literacy, learn how to perform systematic and objective literature searches and reviews, to design robust methodologies and apply appropriate data analyses to test research questions. At the end of the module, students will submit a research proposal which will evidence their competency in designing a research study, and selecting an appropriate method. Students will benefit from knowledge of a number of transferable skills such as decision making, problem solving, data management, critical appraisal of written content and report writing skills.

Additional Information

Everything you need to know about this course!

On the MRes Data Science at the University of Wolverhampton, you will develop a strong combination of advanced research skills, technical data skills, and professional transferable skills.

You will learn how to design, plan, and carry out independent research in data science, giving you experience in research methods, critical thinking, and problem solving. You will also build skills in data management, information literacy, and the critical evaluation of academic and technical literature, helping you to work with evidence in a rigorous and analytical way.

The course will strengthen your ability to write clearly and professionally, particularly through report writing and the communication of research findings to different audiences. You will also develop project management skills, learning how to organise, manage, and deliver a substantial research project effectively.

As an MRes, the course places particular emphasis on self-direction, independent learning, and the ability to work as an emerging researcher. This means you will graduate with the confidence to investigate complex data science problems, evaluate methods and findings critically, and produce high-quality research with academic and professional relevance.

Overall, the MRes Data Science will help you gain skills in decision making, problem solving, data management, critical appraisal, report writing, project management, communication, independent learning, and advanced research practice.

Location Mode Sep intake Fee Jan intake Fee May intake Fee Year
Home Full-time £9088 per year £9088 per year £9088 per year 2025-26
International Full-time £19500 per year £22000 per year £22000 per year 2025-26

The University is committed to a transparent fee structure, with no hidden costs, to help you make an informed decision. This includes information on what is included in the fee and how fees are calculated and reviewed.


If a tuition fee is not showing, we may not offer this intake for this course. Please check the start date information on the course finder for start dates.

Applicants should be educated to Honours Degree level, with a minimum of a 2:2, in Computer Science, Mathematics, Business Studies or an equivalent are with good standard of analytics contents.

UK Applicants who do not hold a recognised degree or an ordinary degree, maybe considered based on a minimum of three year relevant work experience.

International Applicants

Financial support for research study:

Before applying, you should consider carefully how you will finance your studies for the duration of your programme, including tuition fees, research support fees and living costs.


Self-funded:

We are able to take payments in instalments, to spread out the cost of your studies, and it is possible to switch between full-time and part-time modes of study. For more information go to How to pay.

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Postgraduate Research Loyalty Discount:

To students progressing from an undergraduate programme and/or a taught postgraduate programme to a postgraduate research programme, where both courses are University of Wolverhampton Awards.

There is no time limit on how long ago you completed your degree and/or Masters level qualification, as long as the new award is at a higher level.

For full terms and conditions please see: Loyalty Discount for Postgraduate Research Students


Research councils:

The UK Research and Innovation funds postgraduate study in all subject areas on a discretionary basis.


University Research Studentships:

The University offers a very limited number of research stipends, formerly known as bursaries, to research students. Stipends are designed to support specific projects as determined by the Research Institute rather than individual student-led projects. Funds are accessible from the relevant Research Institute or Centre - please contact them directly.


Other sources:

Dennis Turner Opportunity Fund.


You can find more information on the University’s Funding, cost, fee and support pages.

Telephone

01902 32 22 22

Email

enquiries@wlv.ac.uk

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