Artificial Intelligence and Data Science - MSc
Our MSc is part of a £13m 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, tackling skills gaps based on feedback from companies we work with. 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, the Internet of Things and more.
Month of entry
- September, January
Mode of study
- Full time
Fees for 2023/24 academic year
- UK - Full time £10,000 per year.
International - £18,800 per year.
Duration of study
- 1 year
Please note: this course is no longer accepting applications from international students for January 2023 entry
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, 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, 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. You also have the option to gain more real-world experience by participating in the University’s AI and Data Science Ambassador Scheme.
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:
Next Steps
"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."
Course structure
The MSc in AI and Data Science has been co-designed in collaboration with local employers to meet the needs of students from various academic backgrounds – both STEM (science, technology, engineering, mathematics) and non-STEM subjects.
With a September start date, 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).
During the first part of the programme, which runs over the first two semesters, you will study four core taught modules (60 credits). You will learn how to investigate data requirements, data mining and data modelling. You’ll also deepen your understanding of the technologies behind AI, such as machine learning and algorithms.
Depending on your prior experience and in consultation with the Programme Director, you will also choose four optional modules (60 credits), studying two in Semester 1 and another two in Semester 2. This gives you freedom to tailor the course to suit your interests and career aspirations, for example, learning more about the Internet of Things or cloud computing. Please note, however, that if you have not previously studied Computing at undergraduate level, you must choose System Design and Programming. Similarly, students without a suitable mathematics background must choose Mathematics for AI and Data Science.
The second part of the programme gives you freedom to choose between either 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 in to practice and apply the skills and knowledge learned throughout the course.
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).
Semester 1
CSC-40045 Distributed Intelligent Systems - 15 credits
Provides you with the ability to evaluate and design intelligent systems involving the integration and coordination of multiple intelligent systems.
CSC-40054 Data Analytics and Databases - 15 credits
This module equips 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.
OPTIONAL MODULES
(students choose two from four dependent on their prior experience)
CSC-40044 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
CSC-40072 Mathematics for A.I. and Data Science - 15 credits
Introduction to the mathematical concepts relevant to A.I. and Data Science for students from non-mathematical backgrounds.
CSC-40041 Research Horizons - 15 credits
Provides you with the knowledge and skills required to be able to undertake a simple literature review of a research topic related to the Division's research in A.I. and Data Science, and to develop a novel research idea and plan for a research proposal.
CSC-40056 Internet of Things - 15 credits
Provides a practical and theoretical understanding of IoT technologies and their applications in a variety of industries. This includes advanced communications, data analytics and security issues involved in IoT systems and evaluation of their applicability for different types of problems.
Semester 2
CSC-40048 Visualisation for Data Analytics- 15 credits
Equips you with 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.
CSC-40070 Applications of A.I., Machine Learning and Data Science - 15 credits
Equips you with knowledge and experience of a variety of cutting edge A.I. and Machine Learning techniques applied to “real-word” problems and datasets.
OPTIONAL MODULES
(students choose two from three)
CSC-40039 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 students 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. Students 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.
CSC-40038 Collaborative Application Development - 15 credits
Gives an opportunity to overcome the practical difficulties of working with stakeholders and team members to produce applications to solve A.I. and Data Science problems.
CSC-40050 Research and Consultancy Skills - 15 credits
Aims to enhance your skills and knowledge in preparation for your MSc Project or Industrial Placement and for a successful career as an AI. and Data Science professional.
CSC-40102 - AI and Data Science Ambassador Scheme - 15 credits
Allows you to gain academic credit for volunteering as part of an AI and Data Science Ambassador Scheme. You will be placed/volunteer at a local organisation(s) such as school/colleges or relevant small businesses/charities etc. On this placement, you will explain, demonstrate and promote the use of AI and Data Science, consolidating and developing your own skills whilst engaging in support and outreach to the host organisation.
Semester 3
CSC-40040 MSc Project OR CSC-40035 Industrial Placement - 60 credits
After the taught modules have been completed you 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.
Next Steps
Entry requirements
ACADEMIC 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.
ENGLISH LANGUAGE ENTRY REQUIREMENT 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.
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
Next Steps
Funding
Please note, if your course offers a January start date, the January 2023 start date falls in the 2022/23 academic year. Please see the 2022/23 academic year fees for the relevant fees for starting this course in January 2023.
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.
Scholarships
We are committed to rewarding excellence and potential. Please visit our scholarships and bursaries webpage for more information.
It's important to plan carefully for your funding before you start your course. Please be aware that not all postgraduate courses are eligible for the UK government postgraduate loans and, in this case, you would be expected to source alternative funding yourself. If you need support researching your funding options, please contact our Financial Support Team.
Next Steps
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.
Many have also chosen to further their research skills, progressing to study Computer Science PhDs, and you could easily move into a teaching career within secondary, further or higher education.
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
Next Steps
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 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 semester is taught intensively over six-week periods. This means that you will be able to learn the key competencies and skills very quickly. This is particularly important for students who do not have previous experience of studying Computer Science or Maths. In the second semester, each module is taught over a 12-week semester. Here, you will study more advanced topics and put the key skills you have learned in semester one into practice. 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 skills 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. For example, the Research and Consultancy module has previously featured guest lectures from a small business owner, who discussed their experiences, negative and positive, about working with consultants and other small companies, and a Senior Research Developer from Wharton School at the University of Pennsylvania.
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 coursework, such as programming tasks, implementing a web-based application, presentations and reports (e.g., on data storage and user interaction (UI) design).
When it comes to your final assessment, this varies depending on whether you choose 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.
Next Steps
Keele Postgraduate Association
Keele University is one of a handful of universities in the UK to have a dedicated students' union for postgraduate students. A fully registered charity, Keele Postgraduate Association serves as a focal point for the social life and welfare needs of all postgraduate students during their time at Keele.
Hugely popular, the KPA Clubhouse (near Horwood Hall) provides a dedicated postgraduate social space and bar on campus, where you can grab a bite to eat and drink, sit quietly and read a book, or switch off from academic life at one of the many regular events organised throughout the year. The KPA also helps to host a variety of conferences, as well as other academic and career sessions, to give you and your fellow postgraduates the opportunities to come together to discuss your research, and develop your skills and networks.
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.
Through the School’s Employment Steering Group, we are fortunate in that a number of companies, both large and small, local and international, are able to provide work placements, guest lectures, project briefs and feedback on the latest industry trends to ensure course content remains relevant and up-to-date up. Membership in 2021/22 includes 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.
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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.
Next Steps