Taught course

Artificial Intelligence and Data Science

Keele University · School of Computing and Mathematics

Entry requirements

Undergraduate degree in any subject with second class lower (2:2) or an international equivalent. We will also consider students with equivalent industrial work experience.

Months of entry


Course content

Please note, all course information including entry requirements relates to the 2022/23 academic year.

This MSc has been created as part of a £13 million Office for Students initiative to accelerate the number and diversity of skilled artificial intelligence (AI) and data science graduates. It has been designed from both an employer and student perspective, based on our internationally recognised research in multidisciplinary AI and Data Analytics, to provide distinctive and inclusive teaching for students from a wide variety of backgrounds. As part of this, a number of £10,000 Scholarships are available for black, female and disabled students.

To meet employer demand, the number of skilled people in AI and data science needs to increase by 70% by 2020, just to keep pace with demand. There is also an acknowledgement that increasing diversity in the AI workforce is vital to ensure that everyone with the potential to participate has the opportunity to do so, in order to reflect the needs and make-up of society as a whole. This course therefore, has been developed with an Employer Steering Group including organisations such as Synectics Solutions Ltd, Powelectrics, Aspire Housing, SSE Enterprise Energy Solutions, Santander, Caja Ltd Astec IT Solutions, Teal Legal, Hildebrand Technology Limited, Rushkeep, Digital Law UK & Anson Evaluate, so that it not only meets the current demands of industry but also the skills that future industrial AI and data science will require.

We have then combined this with our own research into the barriers that underrepresented and non science, technology, engineering and mathematics STEM) students face when studying AI/Data Science courses, to create the course content, state-of-the-art delivery design, contextual assessments and pastoral support.

This course aims to support students, from both STEM and non-STEM disciplines by providing those without prior experience, the foundations of areas such as programming and mathematics, so that all students can then progress to more advanced areas such as Machine Learning, Data Analytics, Visualisation, Cloud Computing, the “Internet of Things” and Intelligent Systems. During the course, students will also further develop their academic and professional skills and get the chance to work with other students and external organisations to make real interdisciplinary and societal impact in taught modules, an A.I. and Data Science ambassador scheme and as part of an industrial project/placement.


You will be taught in dedicated teaching and laboratory space equipped with cutting edge computer systems. We also have a MakerSpace, a multi-purpose research lab equipped with a variety of robots and aVicon motion-tracking system, a Gaming Lab and a perception lab with state-of-the-art virtual reality equipment. You will also have the opportunity to access data and systems from current research projects such as the Smart Energy Network Demonstrator (SEND) and to visit the Horwood Energy Centre on the Keele campus, the control room for SEND.

Should you wish for an alternative route and/or complete flexibility with your studies, we also offer 100% online Computer Science programmes. Find out more here.

100% Online Computer Science Programmes:

Information for international students

IELTS 6.5 with a minimum of 5.5 in each component . The University also accepts a range of internationally recognised English tests.

If you do not meet the English language requirements, the University offers a range of English language preparation programmes.

During your degree programme you can study additional english language courses. This means you can continue to improve your English language skills and gain a higher level of English.

Fees and funding

For information related to fees and funding, please visit the individual course page on the Keele University website.

Qualification, course duration and attendance options

  • MSc
    full time
    12 months
    • Campus-based learningis available for this qualification

Course contact details