About the course

Overview

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.

Teaching facilities

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:

• MSc Computer Science
• MSc Computer Science with Data Analytics
• MSc Computer Science with Artificial Intelligence

Course structure

Throughout the MSc Artificial Intelligence and Data Science programme you will study a range of both core and optional modules. Indicative modules can be viewed below to provide you with an idea of the modules that may be available to study - we regularly review our teaching to ensure that it is up-to-date and informed by the latest research and teaching methods. 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.

How the course is taught

You will have interactive lectures delivered by academic staff who are experts in the relevant area, as well as tutorial and practical sessions. The course uses a variety of innovative learning tools and methods including working with real clients and problems. This gives students experience and skills they can apply directly to their career and jobs in the future.

Small group teaching is central to how we deliver the course and our staff and students are able to very quickly create supportive working relationships both in person and online.

Each module in the first semester is taught intensively over 6-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 sixteen hours of lectures and practicals each week. Alongside this you will be expected to work independently on exercises and coursework projects, as well as researching course topics online and via the University library.

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.

Funding

Fees and Funding

Office for Students Funded Scholarships for the Msc Artificial Intelligence and Data Science

In 2020, Keele University was one of 18 Universities awarded a share of £13 million to boost the number and diversity of graduates in AI and data science technologies over the next three years. This followed a competitive bidding process run by the Office for Students (OfS) on behalf of the Department for Digital, Culture, Media and Sport (DCMS), Department for Business, Energy and Industrial Strategy (BEIS) and the Office for Artificial Intelligence (OAI).

Our programme offers Scholarships of £10,000 that are available for underrepresented students listed in the following eligibility criteria:

• Black students (Defined in line with the HESA student ethnicity codes)
  • 21 Black or Black British – Caribbean
  • 22 Black of Black British – African
  • 29 Other Black background
  • 41 Mixed – White and Black Caribbean
  • 42 Mixed – White and Black African
    
    
• Disabled students (as defined under the Equality Act 2010)
  
  
• Female students

For 2022 entry, there are 12 Scholarships available.

Prioritising criteria in case of oversubscription

Students with 2 or more underrepresented group criteria will be prioritised initially. Applicants will then be considered by the selection panel where the primary consideration is the candidate’s personal statement (submitted via the form linked below). Panel membership comprises of the Head of School, Director of Education, School Athena Swan Lead and University Athena SWAN Support Officer.

Payment amount and frequency

Successful applicants will receive £10,000 over the course of the academic year.

How to apply

In order to apply for the Scholarship, you must have already applied for a place on the University's MSc in Artificial Intelligence and Data Science course (specific entry requirements can be found on this course page). You can then apply for the Scholarship via the form below:

Application form: https://forms.office.com/r/AueQKaQEYP

Closing date: 1st July 2022.

Please note that this is a competitive process and not all applications will be successful. The Scholarship is available only to students who register for and attend the degree programme. There is no appeals process if you are not successful as the panel’s decision is final. Also, please note that we will not be able to offer feedback. You are welcome to reapply for the next intake if you are unsuccessful.

For September 2022 intake, notifications will be sent at the latest by 21st July 2022.

For further information, please email: e.de.quincey@keele.ac.uk

We are committed to rewarding excellence and potential. Please visit our scholarships and bursaries webpage for more information.

Our expertise

The MSc in Artificial Intelligence and Data Science is taught in the School of Computing and Mathematics.

The School has highly rated research in cutting-edge areas including machine learning & computational intelligence, computational neuroscience and biomedical engineering, evolutionary systems, software and systems engineering and regularly wins funding from the leading UK research funding agencies, ESPRC and BSRC as well as prestigious funding bodies such as the Leverhulme Trust.

In addition, the School hosts monthly research seminars where we invite experts from outside the School to present their latest research to our students and staff.

The School also has several collaborative projects with industry partners including a Knowledge Transfer Partnership with the global automotive company, Bentley Motors Ltd which aims to develop innovative data mining processes that will allow Bentley to exploit the value hidden in the data it owns and collects.

The MSc in Artificial Intelligence and Data Science programme combines these research strengths with our industrial expertise.

Academic staff in the School of Computing and Mathematics include:

• Professor Peter Andras, Head of School
• Professor Fiona Polack, Research Centre Lead
• Dr Theo Kyriacou, Postgraduate Course Director
• Dr Ed de Quincey, Senior Lecturer (Computing)
• Dr Alastair Channon, Reader (Computing)
• Dr Sandra Woolley, Senior Lecturer (Computing)
• Dr Thomas Neligwa, Lecturer (Computing)

Careers

Through our close collaboration with industrial partners, we continually seek to ensure that the MSc in A.I. and Data Science gives our students appropriate technical skills and knowledge - as well as the consultancy, team and project management skills that are required for success in careers where A.I. and Data Science are being developed or used.

The University has a Careers and Employability team who can provide you with advice and guidance about your future career. The team offers specialist workshops, for example 'Options with Postgraduate Study' and Moving on with your PhD', and can also meet you individually to give guidance and support to help you develop your career. We also hold regular careers fairs on campus and informal events where you can meet employers. You will also have access to our database of job opportunities and digital resources such as online psychometric testing.

Athena SWAN

The Athena SWAN Charter is a framework which is used across the globe to support and transform gender equality within higher education (HE) and research. Established in 2005 to encourage and recognise commitment to advancing the careers of women in science, technology, engineering, mathematics and medicine (STEMM) employment, the Charter is now being used across the globe to address gender equality more broadly, and not just barriers to progression that affect women.

Over the past years, we have developed our Equality, Diversity and Inclusion (EDI) agenda and this is now embedded throughout all levels and activities. In September 2020, the School of Computing and Mathematics successfully renewed the Athena SWAN Bronze Award. The School is committed to creating a diverse and inclusive culture in which students are able to thrive, regardless of their gender. You will have the opportunity, if you wish, to attend the annual BCS Women Lovelace Colloquium, LMS Women in Mathematics Day and other Women in STEM events.