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Data Science MSc

2 years with professional placement, starting in September 2025

Prepare for a career in Data Science with specialist skills and knowledge in fundamental statistic techniques and cutting-edge machine learning technologies.

Data science drives a significant proportion of global economic activity from healthcare to finance and technology. It's influencing scientific progress across numerous fields including bioscience, energy and telecommunications.

This course provides you with the computational skills, tools and strong mathematical foundation preparing you for a career in industry. You'll gain practical, analytical and software skills to proficiently gather, process and analyse data, preparing you to tackle complex challenges in modern data science.

To ensure you’re well prepared for the course, you will need a good first degree in a numerate subject such as computer science, mathematics, physics, economics, engineering, or relevant social sciences. You should also be able to demonstrate proficiency in mathematical topics such as calculus and linear algebra, possess some familiarity with probability and statistics, and have a good foundation in programming.

Register your details to watch our short taster lectures and get a taste of the high-quality teaching on our AI courses.

Course highlights

  • Study at a top 10 ranking university on a course developed in consultation with industry experts to ensure you graduate with the skills to be an innovative, ethical, and responsible Data Science specialist.
  • Develop team working skills working in multidisciplinary teams on data-driven projects.
  • Be part of our supportive postgraduate community.
  • Live and study in a beautiful world heritage city.

Specialist facilities

You will have access to purpose-built teaching labs, including a maker lab, allowing you to explore, create, experiment and share software-driven and physical artefact projects in a collaborative workspace context. Complex, data-intensive processes can be analysed over our in-house GPU Cluster. You will have access to most of our specialist labs 24/7.

Project examples

The research expertise in the department allows for a wide-range of subjects for your final project. Recent examples from Data Science students include:

  • Deep learning in high frequency financial trading
  • Spatiotemporal timing predictions in areas with a low density of public transport
  • The impact of mindfulness meditation on multisensory transfer learning

Career prospects

After graduating, you'll be well placed for a variety of careers in data science - from large-scale commercial enterprises, to innovative tech start-ups. Alongside the specialist skills and knowledge you'll gain, our dedicated careers team offers individual guidance and help you decide between employment and further study.

Recent graduate roles include: data scientist, machine learning developer, Python developer and software engineer.

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 2 years. It starts in September 2025 and ends in 2027. 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

Compulsory units

  • Analytic software technologies

    5 credits

  • Applied data science

    10 credits

  • Foundational machine learning

    10 credits

  • Statistical data science

    5 credits

  • Understanding deep learning

    10 credits

Semester 2

Alongside compulsory units, in semester 2 you will also choose 5 credits of optional units, including topics such as humans and intelligent machines, natural language processing and entrepreneurship.

Compulsory units

  • Applied data science

    Continued

  • Bayesian data science

    5 credits

  • Foundational machine learning

    Continued

  • Research and development project skills

    5 credits

  • Spatio-temporal analytics

    5 credits

Summer

Compulsory units

  • Specialist project

    30 credits

Year 2

Semester 1

Compulsory units

  • Professional placement

    60 credits

Semester 2

Compulsory units

  • Professional placement

    Continued

Placement


Apply your technical knowledge and skills to a year working in industry. The placement is taken after the two taught semesters, in an approved company within the UK or abroad. You will learn professional workplace practices, including communication styles, teamwork and task management.

During your placement, you will complete a personal development plan and have regular development and progress reviews with your employer. You will gain an insight into a range of roles available within industry, which may help inform your future career choices.

We have established strong links with many industrial partners of varying size, including Amazon Video, PayPal, JP Morgan, Expedia Group, IBM, Mayden, Netcraft and Deloitte.

Placement opportunities can't be guaranteed but you will receive tailored support from our specialist team to help you secure a placement.

Find out more about going on placement

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

  • Lectures
  • Online resources
  • Practical sessions
  • Seminars
  • Tutorials

Assessment

  • Coursework
  • Essay
  • Multiple choice examination
  • Online assessment
  • Practical work
  • Thesis
  • Written examination
  • Other

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 unit/modules in the first and second semester, with the Summer dedicated to a dissertation. The second semester will have less structured learning as you will start to prepare for your dissertation. Both during the dissertation preparation and the dissertation, supervision will take place at times suitable to you and your supervisor.

You can expect to spend between 9 to 18 hours engaged in structured learning activities per week, of which the majority will be in timetabled sessions on campus, and the remainder online.

In-person teaching and online activities

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

Professional accreditations

By studying a course with a professional accreditation, you could have the chance to get workplace experience, learn about new developments in the industry and apply for membership with the accrediting body. You may also be able to apply for jobs in the industry without having to do any more exams.

This course is accredited by BCS, the Chartered Institute for IT. It is initially accredited as partially meeting the requirements for Chartered Information Technology Professional (CITP) and Chartered Engineer (CEng). In line with BCS guidance, full accreditation will be confirmed once the first cohort of students has graduated from this new course.


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.

‘The course structure is designed so well, and it fits industry demands perfectly.’
Sarah Upendra Chandratreya MSc Data Science (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 your undergraduate degree can be in computer science with a strong mathematical focus, mathematics or any joint mathematics subject. Statistics, physics, astrophysics, engineering or other science degrees with sufficient baseline maths are also suitable. We'll also consider other subjects with sufficient maths content. Programming experience is an advantage.

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 Data Science MSc with professional placement


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

Tuition fees

See the most recent fees for postgraduate courses.

Placement fees

You will normally pay a reduced tuition fee while on a placement period or studying abroad. Find out more about placement fees and study abroad fees.

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

For your course you will also need a desktop or laptop computer running relatively recent versions of either Windows, Mac or Linux operating system. Windows 10, MacOS Monterey or Ubuntu 22.04 LTS are recommended.

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
    Data Science
  • Final award
    MSc
  • Mode of study
    Full-time
  • Course code
    TDUCM-DS04
  • 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