Artificial Intelligence and Data Science - MSc
Our MSc is part of a £30m Government initiative to address the shortage of Artificial Intelligence (AI) and data specialists. Open to students from a wide variety of backgrounds, it draws on our internationally recognised research. You’ll learn about the underlying principles and concepts of AI and data science, including areas of mathematics, data analytics, programming, system design, cloud computing, machine learning, visualisation and more.
Month of entry
- September, January
Mode of study
- Full time
Fees for 2025/26 academic year
- UK - Full time £11,400 per year.
International - £21,400 per year.
Duration of study
- 1 year
Why study Artificial Intelligence and Data Science at Keele University?
Course summary
Digital skills have a crucial role to play in helping to drive growth, productivity and innovation across the rest of the economy, yet one in three businesses say their workforce currently lacks the advanced digital skills they need.
This MSc offers a postgraduate pathway to progress and excel in a career as a data scientist, providing digital skills and knowledge so you can support a diverse range of industries, including medicine, transport, social sciences, biosciences and sports business, to take advantage of the efficiencies and insight new technology can generate.
To ensure course content meets employer needs, the curriculum has been developed with feedback from companies who sit on our Employer Steering Group; local businesses like Synectics Solutions Ltd and Powelectrics, as well as multinationals, such as Santander.
Blending theory, practical teaching and industry experience, it has been purposefully designed to attract students from all walks of life by tackling some of the common barriers facing non-STEM (science, technology, engineering, mathematics) graduates and underrepresented groups. Future diversity in the AI workforce is considered vital, not least to reflect the needs and make-up of society as a whole.
This course aims to support students, by providing the foundations of areas such as programming and mathematics, so that you can then quickly progress to more advanced areas such as machine learning, data analytics, cloud computing, and intelligent systems.
As part of our focus on providing industry-relevant experience, for your final assessment you have the choice of taking either an industrial placement* or tackling an industry-related problem as part of an MSc project.
One of the first UK universities to teach Computer Science back in 1972, Keele takes pride in being at the forefront of computer science education and research today. The School of Computer Science and Mathematics offers an inclusive, dynamic community of experts with access to world-leading research and cutting-edge areas of industry, such as cloud computing, data mining and web technologies.
Each year, we help students transition into a range of science and non-science related careers, including data science, web development, software engineering and computer science, as well as progression to related PhDs.
Other courses you may be interested in:
Embarking on my journey as an international master’s student in AI and Data Science at Keele University has been nothing short of transformative. It’s far more than just academic pursuit; it’s about personal growth amidst a community that feels like family. The program blends cutting-edge labs and real-life projects with an engaging curriculum, all while fostering a vibrant spirit of camaraderie among peers. Keele stands out not just for its academic excellence, but for its warm, inclusive community that prepares you for the world beyond, bridging theory with practical application in a nurturing environment.
Course structure
The MSc in AI and Data Science has been co-designed in collaboration with local and national employers to meet the needs of students from various academic backgrounds – both STEM (science, technology, engineering, mathematics) and non-STEM subjects.
This course is studied full-time over one year. Should you wish for more flexibility with your studies, we also offer 100% online part-time Computer Science programmes, with routes in Data Analytics and Artificial Intelligence (AI).
Please note, if you are beginning the programme in January, you will study the same modules as those listed below, but in a slightly different order.
September entry
During the first part of the programme, which runs over the first two semesters, you will study eight core taught modules (120 credits). In Semester 1, you will begin by learning the fundamentals of programming (Python) and mathematics for AI and Data Science, designed for those without a background in those areas. You will then look at how to apply these skills in areas such as cloud computing and how they relate to the design of distributed intelligent systems.
In the 2nd Semester, you will cover the core areas of databases, data analytics, visualisation and the applications of machine learning and data science, including topics such as deep learning and face/speech recognition.
The second part of the programme gives you the freedom to choose between either a formal academic project supervised by an academic expert from the School or opt for an industry placement*. You’ll be able to discuss with your academic supervisor which type of project or placement is most suitable, based on your performance during the taught modules. Both options will enable you to put into practice and apply the skills and knowledge learned throughout the course.
*Please note that the choice of industry placement will be dependent on your suitability and availability of an appropriate placement.
To achieve the MSc, you must complete 180 credits. There are two interim awards available, depending on how many modules have been successfully completed: a Postgraduate Certificate for any two modules (60 credits); and a Postgraduate Diploma for all four taught modules (120 credits).
Modules
The module details given below are indicative, they are intended to provide you with an idea of the range of subjects that are taught to our current students. The modules that will be available for you to study in future years are prone to change as we regularly review our teaching to ensure that it is up-to-date and informed by the latest research and teaching methods, as well as student voice. The information presented is therefore not intended to be construed and/or relied upon as a definitive list of the modules available in any given year.
Semester 1
Core modules
Cloud Computing - 15 credits
In recent years many organisations have migrated applications to cloud computing providers. This module explores the underlying technologies, the practical and ethical issues involved, and provides you with the ability to plan design and implement cloud-based solutions to common business problems. Reliability and performance concerns are addressed, together with the crucial issues relating to the security and privacy of data stored and managed remotely. Cloud computing is dominated by global software companies that make claims relating both to the efficacy of their products and compliance with global objectives in environmental impacts. You will be able to analyse and objectively assess such claims in coming to reasoned and reflective judgements relating to the appropriateness of cloud-based solutions to a range of problem scenarios.
System Design & Programming- 15 credits
This module provides a comprehensive introduction to system design and programming for those who did not graduate from a computer science or related programme. You will be able to develop programs in a major programming language using principles taught on this course. This module covers:
- The principles and practice of system design in the context of an available set of requirements
- Introduction to programming (algorithms, data structures, data storage and manipulation and user interfaces)
- Introduction to object oriented programming
- The development of computer programs using appropriate technology and including accessing data over the internet
- The use of user interfaces to manipulate and display data
Distributed Intelligent Systems - 15 credits
Our Distributed Intelligent Systems module aims to provide you with the ability to evaluate and design intelligent systems involving the integration and coordination of multiple intelligent systems.
Mathematics for A.I. and Data Science - 15 credits
Ideal for students from non-mathematical backgrounds, this module provides an introduction to the mathematical concepts relevant to A.I. and Data Science.
Semester 2
Core modules
Collaborative Application Development - 15 credits
This module enables you to overcome the practical difficulties of working with stakeholders and team members to produce applications to solve A.I. and Data Science problems.
Visualisation for Data Analytics- 15 credits
You will gain an appropriate understanding of the use of Data Analytics within areas such as health, security, science and business and with a variety of Data Visualisation techniques to interpret trends and patterns in big data
Data Analytics and Databases - 15 credits
This module provides you with the knowledge of database operations and a variety of tools and statistical techniques to enable you to make sense of the exponential growth of big data. You will understand big data issues, advanced analytics and statistical modelling techniques and evaluate their applicability for different types of problems.
Applications of A.I., Machine Learning and Data Science - 15 credits
In this module you will gain knowledge and experience of a variety of cutting edge A.I. and Machine Learning techniques applied to “real-word” problems and datasets.
Semester 3
Optional modules
MSc Project OR Industrial Placement - 60 credits
After the taught modules have been completed you will have the choice to undertake a formal academic project supervised by academic staff in the School or to take an industrial placement in a relevant company or organisation. In both options you will apply the skills you have learned during the taught modules. The decision about the type of project or placement you will do will be made together with the academic supervisors and will be based on your performance during the taught modules.
Entry requirements
Pre-Master's in Computing
The Keele University International College offer a one semester Pre-Master's in Computing programme for international students who do not meet the traditional entry requirements for a postgraduate computing degree at Keele University.
Please visit the Keele University International College for more information on how to apply, entry requirements and course details
Entry requirements
The following section details our typical entry requirements for this course for a range of UK and international qualifications. If you don't see your qualifications listed, please contact us to find out if we can accept your qualifications.
Typical offer
Please ensure that you read the full entry requirements by selecting your qualifications from the dropdown menu below. This will include any subject specific, GCSE/Level 2 Maths, and English language requirements you may need.
Please select your country from the drop-down list below for the full entry requirement information
UK
2:2 degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Bangladesh
60% in a 4-year degree or 3-year degree with a 2-year Master's in any subject from a public university or CGPA 2.8 in a 4-year degree or 3-year degree with a 2-year Master's in any subject from a private university
or
demonstrated relevant professional qualifications or experience
We don’t accept degrees from certain universities, please see our Bangladesh Country Page for more information
You will also need: an English language qualification (see below)
Canada
70% or C or a GPA of 2.5 in a degree (Ordinary or Honours) in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
China
70% in a degree in any subject or 65% in a degree in any subject from a '211' university
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Ghana
Second class degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
India
55% or CGPA 6/10 in any degree of three years or longer
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Kenya
Second class degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Nepal
60% / 2.4 in a 4-year Bachelor's degree in any subject
or
65% / CGPA 2.8 in a 3-year Bachelor's degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Nigeria
Second class degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Pakistan
We accept a range of qualifications from Pakistan. Please visit our Pakistan Country Page for more information
or we will consider demonstrated relevant professional qualifications or experience
You will also need an English language qualification (see below)
South Africa
Second class division 2 / 60% in a Bachelor's degree with Honours in any subject
or
Second class division 1 / 70% in an Ordinary Bachelor's degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Sri Lanka
55% in a Special Bachelor's degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Uganda
Second class degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Zimbabwe
Second class degree in any subject
or
demonstrated relevant professional qualifications or experience
You will also need: an English language qualification (see below)
Pre-Master's in Computing
The Keele University International College offer a one semester Pre-Master's in Computing programme for international students who do not meet the traditional entry requirements for a postgraduate computing degree at Keele University.
Please visit the Keele University International College for more information on how to apply, entry requirements and course details
English language requirements
All of our courses require an English language qualification or test. For most students, this requirement can be met with a 4 or C in GCSE English. Please see our English Language guidance pages for further details, including English language test information for international students. For those students who require an English language test, this course requires a test from Group B.
References
Normally, you will need to provide at least one academic reference to support your application unless you have been out of study longer than two years. If it has been more than two years since you last studied on a degree-level programme, you will normally need to provide an employment reference instead. For more information about Academic References, please see our Postgraduate how to apply web pages.
Personal Statement/Statement of Purpose
Please see our Postgraduate how to apply web pages for guidance on what to include in your personal statement.
Recognition of Prior Learning
The Recognition of Prior Learning (RPL) is a process which enables applicants to receive recognition and formal credit for learning acquired in the past through formal study or work and life experiences.
RPL can also be requested for admission onto the start of a programme in lieu of the admission requirements. For more information, see our Recognition of Prior Learning web pages.
Professional qualifications and work experience
The majority of our courses will consider relevant work experience and/or professional qualifications at the appropriate level, as an alternative to an undergraduate degree for entry. The work experience should be for a sustained period and at a suitable level, based within a relevant sector to your chosen course.
Admissions staff will review your work experience and/or professional qualifications during the assessment of your application to ensure suitability in terms of relevancy, level and appropriate learning outcomes.
General information
The entry grades outlined in this section indicate the typical offer which would be made to candidates, along with any subject specific requirements. This is for general information only. Keele University reserves the right to vary offer conditions depending upon a candidate's application.
"The course was great because it included modules on some of the main areas in industry, for example, data analysis, web technologies and distributed intelligent systems. I graduated from Keele able to begin a web development side business creating industry level websites for small business owners."
Funding
Please note, if your course offers a January start date, the January 2025 start date falls in the 2024/25 academic year. Please see the January 2025 fees for the relevant fees for starting this course in January 2025
Planning your funding
It's important to plan carefully for your funding before you start your course. Please be aware that not all postgraduate courses and not all students are eligible for the UK government postgraduate loans and, in some cases, you would be expected to source alternative funding yourself. If you need support researching your funding options, please contact our Financial Support Team.
For continuing students, fees will increase annually by RPIX, with a maximum cap of 5% per year.
Your career
This conversion master's course is specifically designed for those who want to learn practical skills to apply AI and data science techniques to solve real-world problems – it can be tailored to suit those both with or without prior Computing or Mathematics experience.
Through our close collaboration with industrial partners, we continually seek to ensure that the MSc in AI and Data Science conveys appropriate technical skills and knowledge, as well as the consultancy, team and project management skills employers need.
Essential skills you’ll develop, which are highly valued by employers, include personal drive, prioritising and planning, project management, teamwork, critical thinking, problem solving, evaluating and reflecting upon your experience. This can open up broader management or teaching positions.
Graduates who have joined us from a range of science and non-science disciplines have successfully transitioned into careers in areas such as data science, web development, networking, systems analysis and development, and software engineering. They work for companies as diverse as Bet365, British Airways BAE Systems Applied Intelligence, Bitjam, Capgemini, Hong Kong Esports, Mira, Playtech, IBM, Capita, Lloyds Bank, Rolls-Royce, Vodafone, Morrisons, and the YMCA. You could also consider a teaching career within secondary, further or higher education. Many have also chosen to further their research skills, progressing to study Computer Science PhDs.
Roles you may find interesting include:
- AI strategy manager
- Applied AI developer
- Business analyst
- Computer systems specialist
- Data analyst
- Database administrator
- Data manager
- Data mining and analysis engineer
- Engineering manager
- Head of development
- Information systems manager
- IT consultant
- IT developer
- Lecturer
- Machine learning engineer
- Mobile developer
- Project manager
- Researcher
- Risk analyst
- Senior technical manager
- Software developer
- System engineer
- Teacher
- Technical assistant
- Technical consultant
Teaching, learning and assessment
How you'll be taught
The programme is delivered through a variety of learning and teaching activities designed to develop a blend of academic, professional and practical skills. In addition, you’ll have one-on-one meetings with an individual academic supervisor, which may take place online or face-to-face.
Formal lectures are used to introduce key concepts, supplemented by smaller group tutorials and practical sessions dependent on the topics being covered in the module. This helps to consolidate your understanding of the material and the practicalities of its application in a modern business environment.
Each module in the first two semesters is taught intensively over six-week periods. This means that you will be able to learn the key competencies and skills very quickly and immediately start to apply them. On average you will have around 16 hours of lectures and practicals each week.
Though there are taught components to the course, we place a strong emphasis on student-led learning and research to help develop your independent research and technical skills, with support from teaching staff and technicians. All students are expected to engage in independent study for the duration of the programme and each week we will post digital resources line for you to work through before teaching sessions. Our Virtual Learning Environment gives you online access to a range of digital resources and tools, which includes relevant academic texts via the IEEE Xplore® digital library and eBooks.
You will be taught by experienced, well-qualified staff who are research-active within the discipline, accomplished at working on research-funded projects nationally and internationally, and eager to share their teaching, research and professional experience to help you achieve success in your studies.
Recognising the importance of engaging first-hand with practitioners, where possible, we also invite guest speakers from industry and business to give you a real-life perspective on the topics you’re studying. As part of the funding we have received from the Office for Students to create this course, we attracted a number of supporters from industry such as The BNF Agency, Graide, Reliable Insights, ST-Four, Innov8 Agency Ltd, TMT First and Concentric Solutions, who have provided input into the course and offered a variety of opportunities for students. In addition we often have organisations such as the BBC, HMRC, Capgemini, GroupGTI, the Turing Insitute and Microsoft giving guest lectures and providing opportunities for students in the School.
How you'll be assessed
You will complete formal assessment on all modules. The wide variety of assessment methods used on this programme at Keele reflects the broad range of knowledge and skills that are developed as you progress through the degree programme. This includes unseen examinations, class tests and various pieces of authentic assessments such as coursework (e.g. programming tasks, data science investigations), team working, professional reports and presentations.
When it comes to your final piece of assessment, this varies depending on whether you undertake the Industrial Placement or Research Project.
For the placement, you will complete a 7,000-word report giving a reflective account of your experience of the organisation and the work carried out during the placement; a 2,000-word reflective diary, which can be in the form of a blog; a presentation to your host company management team; and coursework based on information from your employer. Whereas, for the MSc Project, a dissertation of between 10,000 to 15,000 words in length forms your main assessment. You will also prepare a poster describing your interim progress part way through the project.
Our expertise
Teaching staff
The School of Computer Science and Mathematics has a long, well-established history of
industry-focused teaching and internationally recognised research: Mathematics was one of the University’s inaugural subjects back in 1948, while Computing has been taught since 1972, one of the first programmes in the UK.
Our academics specialise in a wide variety of branches of computer science and mathematics, including: computational neuroscience; software engineering; evolutionary systems, ML and computational intelligence; fluid dynamics and acoustics; solid dynamics and elasticity; biomechanics and biomedical engineering; pure mathematics; and statistics.
We are known for our focus on data analytics and data modelling, with pioneering work taking place on the interface of computing, mathematics and engineering, notably in relation to smart energy management and optimisation, and metal detection.
Excellent industry links include the British Computer Society (BCS), the Chartered Institute for IT, and we have worked on several collaborative projects with businesses. For example, we developed innovative data mining processes to allow Bentley Motors Ltd, the global automotive company, to exploit the value hidden in the data it owns and collects. We are also members of The Virtual Cuneiform Tablet Reconstruction Project, an international project to support virtual access to artefacts featuring cuneiform, humankind’s earliest writing.
We have also been fortunate over the years that a number of companies, both large and small, local and international, have been able to provide work placements, project briefs and feedback on the latest industry trends to ensure course content remains relevant and up-to-date up. These have included representatives from Synectics Solutions Ltd, Powelectrics, SSE Enterprise Energy Solutions, Santander, Caja Ltd, and Hildebrand Technology Limited.
Our teaching team includes:
Dr Sangeeta Sangeeta, Lecturer – Sangeeta worked at Heriot watt University and the Department of Computer Science at Jaypee Institute of Information Technology before joining Keele in 2020 as a Lecturer in Data Science. Her research interests include machine learning, software engineering, data science and deep learning. She is currently investigating applications of data mining to automate various software development tasks.
Dr Alastair Channon, Reader (Computing) – Alastair worked in the software industry (at Micro Focus) before embarking on his academic career, which included lecturing at the University of Portsmouth and University of Birmingham prior to his move to Keele University in 2007. His primary research interest is in the open-ended evolution of neurally controlled animats and he is best known for having created the only closed system other than Earth's biosphere to have passed the enhanced statistical ‘ALife Test’ for open-ended evolution. Alastair's recent publications have included significant results on the relationship of mutation rate to population size, with clear implications for biological extinction events, and to fitness, computed over both abstract and biological fitness landscape.
Facilities
The School of Computer Science and Mathematics was established over 50 years ago and is recognised today as being at the forefront of computer science education and research. Proud holders of the Athena SWAN Bronze Award, we have embedded equality, diversity and inclusion (EDI) within both the School and our programmes. We regularly promote events for women studying science, technology, engineering, mathematics and medicine (STEMM) subjects, such as the annual BCS Women Lovelace Colloquium, the national conference for undergraduate and MSc women in computing.
Located in the Colin Reeves Building, our facilities currently house seven computer laboratories comprising around 200 desktop PC, accessible 24 hours a day, every day. Every PC has the current hardware and software needed for all modules on our degree programmes and provide both Microsoft Windows and the Linux operating system. Facilities also include a dedicated VR lab, gaming lab, our own Makerspace with 3D printers, a Vicon motion-tracking system, Raspberry PIs, Arduinos and dedicated PCs. We provide various web servers and a cloud computing facility for student use. We also host a high-performance CUDA GPU Supercomputer Cluster for use across campus.
The Overclockers UK Gaming Lab
Based in the Colin Reeves building, this state-of-the-art gaming station laboratory is named after its sponsor, who donated 24 high-spec gaming PCs. These are available for use by students during their lectures and exclusively to Keele Esports Society members in the evenings as a training facility. The Society is open to students who are interested in all aspects of competitive gaming, on both the professional scene and the amateur level.
Central Science Laboratory (CSL)
An entire floor of the University’s £34m Central Science Laboratory (CSL) is fully equipped with PCs featuring all our necessary software and is used for practical lab sessions. CSL opened its doors to students in September 2019 and provides 5,300m2 of modern, co-located science laboratories. Over £2m alone has been spent on industrial research-grade analytical and laboratory equipment that will be used by students in their day-to-day laboratory teaching. Access to state-of-the-art facilities and high specification equipment will ensure you are well prepared for scientific or industrial employment post-graduation. The environment mirrors the multi-faceted nature of working life and the shared space allows group working and collaboration between disciplines, building the skills and experience much valued by employers.
Living Lab
Our unique self-contained campus, with over 600 acres of grounds including forests and lakes, has provided an ideal setting to establish itself as a testbed for real-world teaching, learning and research opportunities as a ‘true Living Lab’. Featured as a national best practice case study in the promotion of sustainability exchange, initiatives such as the SIMULATE (Smart, Infrastructure and Mobility Urban Laboratory and Test Environment) and Smart Energy Network Demonstrator (SEND) projects, contributed to Keele being named Global Sustainability Institution of the Year (International Green Gown Awards, 2020).
SIMULATE, which received funding from the Government’s SMART Place Live Labs initiative, is focused on how to design and maintain a smart highways network. The £15m SEND programme was the first of its kind in Europe to demonstrate how smart energy technologies can support ‘intelligent’ energy generation, distribution, storage, forecasting and energy balancing. Our researchers have worked with businesses on a range of projects: anomaly detection for Internet of Things applications; use of deep reinforcement learning techniques for a smart energy management system; data analytics solutions for the Industrial Internet of Things; and Digital Twins.
Digital Society Institute
Keele’s new Digital Society Institute is a collaborative research centre focused on data and digital technology that will allow companies in the business, health, and cultural sectors to innovate and expand in a competitive and dynamic business environment. Launching in 2022, the Institute will be based within IC7 and will have access to a Data Visualisation Suite, office space, and hi-tech meeting and collaboration space. The facility, which will enable businesses to keep pace with fast-changing technologies, is expected to support over 400 SMEs over an 18-month period. Specialist equipment it will host includes: a state-of-the-art £330,000 high-performance computing cluster for data-driven research; a new VR/Interaction Laboratory; VR headsets; high-specification computers; a CAVE environment; eye-tracking glasses; 360-degree cameras; a high resolution hand-held 3D scanner; and a 3D printer.