Data Science MSc
- Computing and information systems
- Postgraduate
Embrace the career opportunities emerging in the rapidly-expanding data science field with the Data Science MSc from Kingston University. This degree has been accredited by the British Computer Society (BCS), the Chartered Institute for IT.
This course has flexible entry points and has been designed for a variety of disciplines and backgrounds. In particular, if you’re coming from a non-computing or mathematics discipline, you should head over to our Data Science Conversion MSc page.
Learn to use computing and statistical methods to extract insights from unstructured data
Data science is one of the most rapidly-expanding areas of employment globally, due to fast-paced and ongoing developments in computer systems and data gathering.
At our Penrhyn Road campus, you will have access to a modern environment with the latest equipment, including:
- dedicated postgraduate computing laboratories, fully-equipped with fold-flat LCD screens, data-projection systems and high-spec processors
- industry-standard development software and tools, such as Python, Scikit, Learn and Tensorflow
- the learning resources centre, offering subject libraries, online database subscriptions and resource materials
Our dedicated IT technicians support our labs and are always on-hand to provide assistance.
Kingston is just a 30-minute train journey from central London, where you can access a wealth of additional libraries and archives. These include the British Library and the Institute of Engineering and Technology.
Being given the chance to become one of the few black women entering the tech field is a significant achievement, especially given the lack of diversity in the field. The support from lecturers, the resources, the workshops and the diverse motivated classmates have made it easier. I'm excelling in the course and I’m incredibly grateful that the scholarship gave me the chance to pursue my passion. Transitioning from biomedical science to data science was a challenge I never expected to take on, but here I am, and I'm forever thankful for the opportunity!
Why choose this course
Large data sets are widespread in business, science and government. Consequently, there is an increasing demand for data-savvy professionals, both in industry and in research, who are able to make sense of complex datasets, build models and apply them to the solution of relevant problems.
This course builds on the established strengths of the mathematics and computer science programmes at Kingston. It develops a multidisciplinary approach to the computational analysis of data. You will get the opportunity to develop your skills in a way which will prepare you for a variety of careers in this fast-growing and exciting area. You will also get to take advantage of opportunities for exposure to cutting-edge examples and exercises.
Like many MSc courses in the School of Computer Science and Mathematics, Data Science benefits from a diverse community of learners. Typically, each 30 credit module runs over five weeks with two timetabled days each week, giving you some flexibility to work part-time around your studies.
If you’re coming from a non-computing or mathematics discipline, we also offer a conversion course. This was designed to support the government's response to the shortage of data science and artificial intelligence specialists in the UK. Please visit the Data Science Conversion MSc webpage for more information.
International Success Support Scholarship
If you are an international student, you may be eligible for a £2,500 International Success Support Scholarship for this course, for September 2026 start only.
Accreditation
This degree has been accredited by the British Computer Society (BCS), the Chartered Institute for IT. Accreditation is a mark of assurance that the degree meets the standards set by BCS. An accredited degree entitles you to professional membership of BCS, which is an important part of the criteria for achieving Chartered IT Professional (CITP) status through the Institute.
Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords. This degree is accredited by BCS for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional.
Course content
The multidisciplinary nature of data science is reflected in this MSc programme. The combination of modules in data management, analysis, modelling, visualisation and artificial intelligence (AI), are taught by a cross-disciplinary team. The team's collective expertise encompasses mathematics, statistics, AI and machine learning, information management, and user experience design.
For a student to go on placement, they are required to pass every module first time with no reassessments. It is the responsibility of individual students to find a suitable paid placement. Students will be supported by our dedicated placement team in securing this opportunity.
Modules
The programme is made up of four modules each worth 30 credit points plus an individual project worth 60 credits. The optional Professional Placement can be undertaken following completion of the other modules. The optional Professional Placement taken during an additional year will give 120 credits.
Please note that this is an indicative list of modules and is not intended as a definitive list.
Core modules
Professional placement
Professional placement
Career opportunities
Graduates from this course go on to pursue careers contained within the more generic data science umbrella. For example, they may become data engineers, data analysts and machine learning engineers.
Work placement scheme
This course, like many postgraduate courses at Kingston University, enables students to integrate a 12-month work placement into their course. You are responsible for finding and securing your own professional placement, which can be highly competitive but also incredibly rewarding. It is very important to prepare yourself if this is the route you wish to take. Employers look for great written and oral communication skills and an excellent CV/portfolio. As the work placement is an assessed part of the course, it is covered by a Student Route visa.
We work with a variety of employers such as hospitals, community health care, NHS foundation trusts, academic publishers, and pharmaceutical companies. Many of which also offer professional experience opportunities for the students on this course.
Careers and recruitment advice
The Faculty has a specialist employability team. It provides friendly and high-quality careers and recruitment guidance, including advice and sessions on job-seeking skills, such as CV preparation, application forms and interview techniques. Specific advice is also available for international students about the UK job market and employers' expectations and requirements.
The team runs employer events throughout the year, including job fairs, talks from industry speakers and interviews on campus. These events give you the opportunity to hear from, and network with, employers in an informal setting.
Teaching and assessment
The learning, teaching and assessment strategies reflect the programme aims and learning outcomes, student background, potential employer requirements, and the need to develop a broad range of technical skills with the ability to apply them appropriately.
The use of coursework emphasises more authentic assessments, which could be, for example, from business or research contacts in local SMEs or colleagues working with "big data" in the NHS, with appropriate ethical and IP approval, as necessary. For example, students will typically create applications, documentation and visualisations, writing reports and giving presentations. Students will have the opportunity in some assignments to identify topics and target audiences in consultation with teaching staff which allows them to express their individuality and appreciate the diversity within course. In this way, as they progress through the course, students are guided and supported to assemble a portfolio of tangible outputs which evidence, explicitly, the knowledge and skills they have gained and which may be used to demonstrate their capabilities to future employers in a format that can be influenced by the students' own preferences.
Fees and funding
Additional course costs
Some courses may require additional costs beyond tuition fees. When planning your studies, you’ll want to consider tuition fees, living costs, and any extra costs that might relate to your area of study.
Your tuition fees include costs for teaching, assessment and university facilities. So your access to libraries, shared IT resources and various student support services are all covered. Accommodation and general living expenses are not covered by these fees.
Where applicable, additional expenses for your course may include:
Fees for future course years
Part time
If you start your second year straight after Year 1, you will pay the same fee for both years.
If you take a break before starting your second year, or if you repeat modules from Year 1 in Year 2, the fee for your second year may increase.
Funding support for postgraduate students
If you are a UK student living in England and under 60, you can apply for a loan to study for a postgraduate degree. Find out more through the government's website.
Scholarships and bursaries
For students interested in studying Data Science MSc at Kingston, there are several opportunities to seek funding support:
International Success Support Scholarship
The International Success Support Scholarship provides £2,500 towards tuition fees if you are an international student starting in January or September 2026 on this course or selected others. Eligible postgraduate students receive the award in their first year, helping to support their academic journey from day one.
You don’t need to apply separately. If you’re eligible, the scholarship will automatically be applied to your tuition fee invoice, empowering you to focus on achieving your goals at Kingston University.
For more details, please visit the International scholarships page.
How to apply
Before you apply
Please read the entry criteria carefully to make sure you meet all requirements before applying.
How to apply online
Use the course selector drop-down at the top of this page to choose your preferred course, start date and mode, then click 'Apply now'. You will be taken to our Online Student Information System (OSIS) where you will complete your application.
If you’re starting a new application, you’ll need to select ‘new user’ and set up a username and password. This will allow you to save and return to your application.
Application deadlines
We encourage you to apply as soon as possible. Applications will close when the course is full.
Information required to confirm your place
If English is not your first language, we will require proof of your proficiency to allow us to confirm your place on the course. This will generally be either an IELTS or TOEFL test certificate, which can be forwarded to us after you have submitted your application. If you do not hold a formal English language qualification, please indicate how you have acquired your proficiency in written and spoken English.
After you have applied
If the postgraduate admissions tutor requires further information or wishes to invite you to further assessment by interview they will contact you directly. You will then hear whether your application has been successful.
If you do not clearly meet the standard entry requirements and the admission tutor wishes to see a portfolio from you, you will be sent an email asking you to upload your portfolio to your Kingston University OSIS account. Further details on how to do this will be provided at the time.
Course changes and regulations
The information on this page reflects the currently intended course structure and module details. To improve your student experience and the quality of your degree, we may review and change the material information of this course. Find out more about course changes
Programme Specifications for the course are published ahead of each academic year.
Regulations governing this course can be found on our website.
