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Mathematics with Data Science for Industry MSc

1 year, starting in September 2025

This course is closed to applications for September 2025 entry.

Stand out to employers with a strong understanding of how applied maths, machine learning and data science can solve problems in a broad range of industries.

The cutting-edge application of mathematics in industry incorporates modelling, analysis and interpretation using methods from applied mathematics together with machine learning and data science. We’ll provide you with essential skills for a career as an applied mathematician working in a range of industries.

Who this course is for

If you're a graduate in mathematics or a highly mathematical discipline, who would like to develop and apply mathematical and computational skills to tackle complex real-world problems, this course is for you. It provides training in machine learning, statistics, mathematical modelling, computational mathematics and collaborative problem-solving in industry.

Course highlights

  • Enhance your mathematical skills by studying a wide range of taught units in applied maths techniques, mathematical modelling, data science, machine learning and scientific communication.
  • Gain genuine experience of collaborative problem solving from group projects with other students or a project with one of our industrial partners.
  • Undertake an optional 12-month placement with a company or public sector body to improve your employability.
  • Be part of our supportive postgraduate community.
  • Live and study in a beautiful world heritage city.

Summer research project

A key element of the course is the opportunity to work on a real project with one of our industry partners. This may include some time based at an external organisation. During the course our industry partners will pitch potential projects and you will be supported to apply for one. However, an industry project is neither mandatory nor guaranteed so academic projects are also available.

Some of our recent industry partners include the Met Office, BT, NHS and VisitSomerset.

Examples of projects include:

  • Forecasting future energy demand with machine learning
  • Statistical learning to predict phosphate in unmonitored water bodies
  • Modelling sensor array optimisation for Proton Beam Therapy

Recent graduates from the Department are working in a range of roles at large companies and data science start-ups or have gone on to do PhDs in areas such as applied maths, numerical maths and machine learning.

Career prospects

Mathematics and data are fundamental to modern science and many industries are looking for graduates who can work across these fields. You'll also have acquired the essential foundation for further postgraduate study and research within related fields. Our dedicated careers team offers individual guidance to help you decide between employment and further study.

Find out more on maximising your employability while at Bath.

Find out more about studying at Bath

2025/26 Academic Year


Before you apply for a course, please check the website for the most recently published course detail. If you apply to the University of Bath, you will be advised of any significant changes to the advertised programme, in accordance with our Terms and Conditions.

We understand that you will want to know more about the shape of the academic year. We work hard and plan for different scenarios, to be able to welcome you to the University of Bath at the start of each semester.

Course structure

This course lasts 1 year. It starts in September 2025 and ends in 2026. Welcome week starts on 22 September 2025.


Occasionally we make changes to our programmes in response to, for example, feedback from students, developments in research and the field of studies, and the requirements of accrediting bodies. You will be advised of any significant changes to the advertised programme, in accordance with our Terms and Conditions.

Year 1

Semester 1

In semester 1, alongside compulsory units you will choose 10 credits of optional statistics units. If you do not have extensive prior knowledge of undergraduate statistics you will take the units Statistics for data science and Statistical modelling. If you have studied a lot of statistics before, you will take the units Classical statistical inference and Statistical modelling.

Compulsory units

  • Foundations and applications of machine learning

    10 credits

  • Principles and practice of industrial mathematics

    10 credits

  • Programming for data science

    10 credits

Semester 2

In semester 2, alongside the compulsory units, you will choose 10 credits of optional units depending on your expertise or interests. Options include topics such as Bayesian data analysis and Applied statistics or Inverse problems and optimisation.

Compulsory units

  • Collaborative industrial research

    5 credits

  • Foundations and applications of machine learning

    Continued

  • Mathematical modelling for industry

    5 credits

  • Principles and practice of industrial mathematics

    Continued

Summer

Compulsory units

  • Dissertation

    30 credits

Placement


This is the one-year version of the course without placement. We also offer this course with a placement year, giving you the opportunity to gain work experience as part of your degree.

Learning and assessment

You’ll be taught and assessed by a variety of methods and it will vary between units. These methods are designed to promote in-depth learning and understanding of the subject.


Learning

  • Research project
  • Lectures
  • Online resources
  • Seminars
  • Tutorials
  • Workshops
  • Real-life case studies

Assessment

  • Coursework
  • Dissertation
  • Online assessment
  • Presentations
  • Seminar
  • Written examination

These lists are to give you an idea of some, but not all, of the learning and assessment methods used on this course. They are not exhaustive lists and methods are subject to change.

Learning and teaching

Overall workload

You should expect to spend approximately 35 to 40 hours a week studying on your course. These hours consist of structured activities and independent learning. You will experience a mix of in person teaching, that will take place on campus, and structured online learning delivered through the University’s virtual learning environment.

Structured learning activities

MSc programmes deliver taught units in the first and second semesters, with the summer dedicated to a dissertation. During the dissertation supervision will take place at times suitable to you and your supervisor.

Typically, you can expect to spend approximately 12 hours on structured learning activities per teaching week. The majority of these activities will be in timetabled sessions on campus. A small proportion may be online.

In-person teaching and online activities

Timetabled sessions delivered in person on campus will be a mix of lectures, seminars, tutorials, workshops and practical laboratories. Online activities may include following a recorded lecture, or other learning materials, or joining a timetabled live interactive session through Teams or Zoom.

Independent learning

The remainder of your time outside these structured activities will be spent in independent learning which includes individual research, reading journal articles and books, working on individual and group projects, preparing coursework assignments, preparing presentations, or revising for exams.

To support you in your studies you will be able to access, outside of timetabled learning, facilities on campus and in Bath such as study spaces, computers, and the Library.

Recognition of professional qualifications


As well as being recognised as a higher academic qualification, a number of our degrees are also accredited by professional bodies in the United Kingdom. An accredited degree may entitle you to work in a specific profession within the UK, and abroad (where there are reciprocating arrangements with professional bodies in other countries).

The requirements to practise a profession vary from country to country. If you wish to practise your profession outside the United Kingdom, you are advised to confirm that the UK professional qualification you seek is valid in the country in which you are intending to work.

‘Seeing the real-world application really shows that what I'm learning has genuine effects and importance within both industry and the world as a whole.’
Daniel Thompson Mathematics with Data Science for Industry MSc (Graduating year, 2024)

Entry requirements


Origin of qualifications

British qualifications

You should have a first or strong second-class bachelor’s honours degree or international equivalent.

To apply for this course, you should have an undergraduate degree in mathematics, physics or engineering.  

We will also consider undergraduate degrees in other disciplines provided there is a substantial mathematical component.

We may make an offer based on a lower grade if you can provide evidence of your suitability for the degree.

If your first language is not English but within the last 2 years you completed your degree in the UK you may be exempt from our English language requirements.

English language requirements

  • IELTS: 6.5 overall with no less than 6.0 in all components
  • The Pearson Test of English Academic (PTE Academic): 62 with no less than 59 in any element
  • TOEFL IBT: 90 overall with a minimum 21 in all 4 components

You will need to get your English language qualification within 24 months prior to starting your course.

If you need to improve your English language skills before starting your studies, you may be able to take a pre-sessional course to reach the required level.

Fees and funding

Fees and funding information for Mathematics with Data Science for Industry MSc


Fees

Your tuition fees and how you pay them will depend on whether you are a Home or Overseas student.

Learn how we decide fee status

Extra costs

If you receive an offer, you will need to pay a non-refundable deposit of £1,000 when you accept to secure your place. This will be deducted from your tuition fee when you register.

IT requirements

Computational work will be an integral part of the course. Therefore, you are strongly encouraged to get up to speed with Python before starting the MSc and to bring a laptop computer with the Windows, Mac or Linux operating system and an up-to-date Python installation.

How to pay

Tuition fee loans

If you are studying a postgraduate course, you may be able to take out a loan for your tuition fees and living costs.

Read more about tuition fee loans

Scholarships and bursaries

You could be considered for a bursary or scholarship to help you study at Bath. You do not have to pay it back.

Read more about bursaries and scholarships

Other payment options

You can pay your tuition fees by Direct Debit, debit card, credit card or bank transfer. You may also be eligible for a student loan to help you pay your fees.

Read more about your payment options

Budgeting

You will need to budget at least £100 for the cost of photocopying, printing and binding. You will also need to budget for the cost of textbooks.

Some courses involve visits away from campus and you may be required to pay some or all of the costs of travel, accommodation and food and drink.

If you’re on a placement, you’re responsible for your own travel, accommodation and living costs. You should also consider the financial implications if you go on an unpaid or overseas placement.

Application information


  • Course title
    Mathematics with Data Science for Industry
  • Final award
    MSc
  • Mode of study
    Full-time
  • Course code
    TDUMA-MD01
  • Department
  • Location
    University of Bath
    Claverton Down, Bath BA2 7AY
  • Home application deadline
    31 August 2025

    We recommend you apply early as we may close applications before the deadline if a course is full.

  • Overseas application deadline
    31 July 2025

    We recommend you apply early as we may close applications before the deadline if a course is full. We may consider late applications but if you need a Student Visa to study in the UK, you will need time to apply for and receive your visa to be in the UK by the start of the course.

  • Application eligibility
    Home and Overseas students are eligible to apply
  • Regulator

Course enquiries