If you want to improve the world through the responsible use of data, the MSc in Data Science will give you the skills to do so. You will learn how to understand, in depth, the computational and statistical principles of modern data science and be skilled at the rigorous and ethical application of these techniques to real-world challenges.

Whether you have a background in numerate sciences, engineering, or computer science, the programme will provide you with the skills to succeed in this exciting and fast-moving discipline and will equip you with excellent employment prospects to pursue roles in industry as either a data scientist or data engineer as well as for research and development roles.

This MSc aims to:

  • Equip you with the ability to work across disciplinary boundaries in the effective application and deployment of data-intensive solutions in a variety of contexts.
  • Give graduates a breadth and depth of knowledge and skills in computational, machine learning, and statistical principles and the capability for insightful large-scale data analysis, so you will be able to specify and implement analytical pipelines for real-world data at scale.
  • Provide you with a good understanding of the ethical issues in the application of contemporary data science techniques to real-world challenges, including arguments about the risks, benefits and disadvantages arising from the deployment of these technologies.
  • Enable you to independently initiate data science projects specified at a high-level perspective, leading them from scoping onward to completion, while exercising appropriate project management methods and maintaining stakeholder engagement.

The MSc in Data Science has been co-designed with industrial partners and is highly relevant to rewarding employment opportunities. There is a strong emphasis on responsible innovation and ethics to encourage you to use your knowledge and skills for societal good in the workplace or through further research. The course is closely associated with excellent research in the University, ensuring leading-edge teaching.

Programme structure

You will take either a 20-credit unit in Software Development: Programming and Algorithms, or, if you already have software development skills, a 20-credit unit in Statistical Computing will be required.

The remainder of the MSc consists of the following compulsory units:

  • Large-Scale Data Engineering (20 credits)
  • Technology, Innovation, Business, and Society (20 credits)
  • Introduction to Artificial Intelligence (10 credits)
  • Introduction to Data Analytics (10 credits)
  • Advanced Data Analytics (20 credits).

The final compulsory unit, a Data Science Mini-project (20 credits), is a group activity which will be aligned, wherever possible, with an external client.

To complete your studies, a 60-credit individual research or implementation project can be chosen from a selection proposed by project supervisors. This unit will provide you with first-hand experience in planning, running, documenting, and presenting a substantial piece of original work in the field of Data Science. The aim of this unit is to give you a substantial opportunity to integrate material from all taught units and demonstrate the breadth and depth of your learning on the MSc.

The scheduling of units depends on whether you choose the two- or three-year study option. Note that tutor-led sessions will normally take place during UK office hours only. For the online MSc taken over two years, on average the number of timetabled contact hours per week will be between two and four (occasionally rising to five if you have a scheduled personal tutorial) - these are synchronous sessions where you need to be online to participate in meetings with other students and academics. There are also asynchronous sessions.

Visit our programme catalogue for full details of the structure and unit content for our online MSc in Data Science.

Entry requirements

An upper-second class honours degree (or international equivalent) in a numerate science, computer science, or engineering. Examples of acceptable degree titles include, but are not limited to Computer Science, Computing, Mathematics, Statistics, Operations Research, Data Science, Software, Engineering, Psychology, Physics, Chemistry, Genetics, Biology, Neuroscience, Economics, Finance, Accounting, Econometrics, AstroPhysics, Geology / Earth Sciences, Civil, Engineering, Mechanical Engineering, Aeronautical Engineering, Chemical Engineering, Systems, Engineering, Electronic Engineering, Electrical Engineering, Nuclear Engineering, Manufacturing, Engineering, Software Engineering, Mining Engineering or Medicine

We will consider applicants whose grades are slightly lower than the programme's entry requirements, if they have at least one of the following:

  • evidence of significant, relevant work experience;
  • a relevant postgraduate qualification.

If this is the case, applicants should include their CV (curriculum vitae / résumé) when they apply, showing details of their relevant work experience and/or qualifications.

See international equivalent qualifications on the International Office website.

Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.

Go to admissions statement

If English is not your first language, you will need to reach the requirements outlined in our profile level C.

Further information about English language requirements and profile levels.

Fees and funding

UK: part-time (two years)
£8,200 per year
UK: part-time (three years)
£5,467 per year
Overseas: part-time (two years)
£17,100 per year
Overseas: part-time (three years)
£11,400 per year

Fees are subject to an annual review. For programmes that last longer than one year, please budget for up to an 8% increase in fees each year.

More about tuition fees, living costs and financial support.

Alumni discount

University of Bristol students and graduates can benefit from a 25% reduction in tuition fees for postgraduate study. Check your eligibility for an alumni discount.

Funding for 2024/25

Further information on funding for prospective UK and international postgraduate students.

Career prospects

Graduates from this MSc will be keenly sought after in roles such as lead data scientists or lead data engineers, capable of critically evaluating and synthesising research literature, developing and deploying scalable data-processing systems, and communicating with others in their field and in other disciplines. Top graduates from this degree will be able to proactively advance the development of data science and related technologies.

The programme content has been co-designed with, and will be continually revised and updated with, our industrial partners, as represented by the Data Science Industrial Advisory Board. We expect a sizeable proportion of the students on the MSc to be in employment while studying, and the overwhelming majority of them to retain these posts after completion.