Data Science virtual open day

Welcome to the School of Computing and Mathematics!

Thank you for your interest in our UG Programmes in Data Science. Please explore the videos below to discover more about our course and environment. You can meet some of our students and academics and find answers to some frequently asked questions.

If you need more information, please feel free to get in touch with our Admissions Tutor ( You can find all our contacts at the bottom of this page or you can chat to staff and students via Unibuddy.


Our School is located in the Colin Reeves Building, where we host our computer labs (open 24/7), our high-performance cluster (used for research and projects) and a dedicated gaming lab (the Overclockers Lab). An entire floor of our brand new Central Science Laboratories is fully equipped with PC's and all necessary software is also used for our practical labs throughout teaching semesters.


Data Science is a broad, interdisciplinary field unifying statistics, data analysis, machine learning, and software development. Our Data Science graduates are trained from first principles in Mathematics and Computer Science and the two disciplines are blended seamlessly throughout your degree.

As a data scientist you will be a producer of knowledge from data.

Fiona Polack, Professor of Software Engineering, talks about the structure of our course and the opportunities it can offer to you.

Please Note: BSc Data Science with Applied Business Informatics is a Single Honours degree programme and has now been validated. 

You will study fundamental mathematical and statistical techniques alongside modern software development methods. You will have the opportunity to apply your learning immediately using real-world datasets.

We do not assume any specific previous knowledge in mathematics or statistics, and your instructors will provide all the needed preliminary concepts.

In your first year, you will focus on core skills and academic and personal competences; our first semester, in particular, presents the fundamental concepts and techniques for Data Science to bring everyone from diverse backgrounds to a common understanding of the discipline. During your second and third year, the focus will progressively shift towards characterising and advanced modules.

Each taught module will include traditional lectures, with all support material provided via our virtual learning environment (KLE). Depending on the subject matter and level of the module, modules will include practical sessions in our computer laboratories, tutorials or directed reading, and group project sessions. Each student will also have regular opportunities to talk through particular areas of difficulty, and any special learning needs they may have, with their Personal Tutors or module lecturers on a one-to-one basis.

Assessments, again depending on the specific module, will include unseen examinations, class tests or coursework.



An important part of your degree, where we hope you can unleash your creativity and make full use of all the skills you've gained, is the final project in your third year. Under the guidance of an experienced colleague, you can choose your own topic or you can explore one of our research themes.

Keele is at the forefront of research and is also in the unique position of hosting the first living laboratory for energy-efficient technologies: the multi-million pound Smart Energy Network Demonstrator (SEND). You can watch a brief introduction by Professor Zhong Fan.



Lab locations

  • Reeves (CR10) - 74 PCs
  • Babbage (CR12) - 28 PCs
  • Knuth (CR113) - 20 PCs
  • Projects (CR7) – 11 PCs / 1 Apple iMac
  • Computer Science Study – 7 PCs / 1 Apple iMac
  • Maths Study – 16 PCs

iMac spec

21.5 inch screen
I5 processor
1 TB hard drives

PC specs

Windows 10 / Ubuntu Linux

Lenovo 8th Gen i7 16GB NVMe SSD
HP Elite All in One 23 inch monitors
I7-6700 3.40Ghz processor
AMD Radeon R9 GPU graphics card


USB 3.0

  • 24 PCs
  • 24 hours access for Gaming Society
  • Normal University working hours for SCM students


I5 8600K CPU processor
Nvidia GTX 1070 GPU graphics card
16GB 2400MHZ RAM
Asus Rog peripherals including headsets
Asus Rog 144hz 24 inch monitors

HTC Vive Pro (Wireless Wigig adaptor for free roam) x 2 controllers

PC Spec

I7-8700k CPU (water cooled) processor
16GB 3200MHZ RAM
Nvidia GTX 1080TI
27 inch monitor

  • 13 PCs
  • Various hardware e.g. Rasberry Pi/Arduino/EMG Spiker Boxes/Quadcopters, including 2 x 3D printers: Ultimaker 2 (filament) and Formlabs Form 1+ (resin)
  • 3D scanner


Our Director of Recruitment and Admissions Tutor, Dr Marco Ortolani, will be happy to answer any further questions you might have. His email address is You can also contact the School Office, or, for general admissions enquiries,

You can also follow us on Twitter and Facebook.