School of Engineering, Computing and Mathematics

MSc Artificial Intelligence

MSc Artificial Intelligence (AI) incorporates elements of the theoretical underpinnings of AI along with exposing students to the practical considerations of constructing AI software tools. Students will study deep technical modules on topics including machine learning, computational intelligence, computer vision and big data, while studying modules on applied AI and robotics to gain an appreciation of the wide range of industrial applications AI has in the modern world.

Find out more about your eligibility for a postgraduate loan

You may now be eligible for a government loan of over £11,000 to help towards the cost of your masters degree.

Find out more about your eligibility for a postgraduate loan

International postgraduate taught open day

Discover how this masters-level degree can help your future career by talking with us at our international postgraduate open day.


Register for the international postgraduate open day


Key features

  • The programme has the potential for students to tailor their degree towards the industry in which they wish to apply their AI knowledge by selecting and exploring industry-relevant data sets and problems.
  • A combination of module types, including technical modules facilitating a deep-dive of cutting-edge AI technologies and providing experience of constructing AI software from first principles, alongside workshop modules providing insight into the field of AI as a whole. Each Semester is comprised of two technical modules and a workshop module.
  • An embedded research-informed teaching experience offering state-of-the-art knowledge, skills and practice, delivered by internationally recognised and world-leading academics. Students will work directly with these academics, receiving education, support and guidance from researchers at the forefront of AI research.
  • Excellent facilities for conducting research and project work in AI and robotics, including a range of state-of-the-art robotics laboratories, recently-updated computing facilities and the forthcoming new Engineering Design Facility, all of which provide an inclusive learning environment.
  • The programme incorporates a substantial element of practical and production-based work, resulting in an end product of industrial quality that solves a relevant problem. The programme’s assessment is inclusive, being completely coursework and practice based, and providing authentic and holistic means of assessing progress.
  • We promote learning through practice and doing, and a prominent feature of the programme is a dissertation module that enables students to draw together the rest of their taught content to produce outputs of a professional and publishable standard.
  • As a result of our industrial links students have excellent employment opportunities with a wide variety of organisations. These include both providers and consumers of AI.

Course details

  • Year 1
  • Students will learn a variety of cutting edge AI topics including machine learning, computational intelligence, computer vision and robotics. In all modules there is a focus on industrial problem solving with AI, and you will complete a dissertation in which you will conduct a deep exploration of a topic of your choice. Throughout your studies you will gain practical experience of constructing AI using both existing tools and innovating new methods from first-principles.

    Core modules
    • AINT515 Artificial Vision and Deep Learning

      This module will provide an advanced knowledge of artificial vision systems for autonomous robots. It will be underpinned by current theoretical understanding of animal vision systems and computational models. This module will introduce the use of deep-learning neural networks in vision systems.

    • AINT516 Topics in Advanced Intelligent Robotics

      This module introduces the research activities of the Centre for Robotics and Neural Systems (CRNS). It is taught by CRNS members who lead thematic workshops on their own areas of expertise, such as swarm robotics, cognitive robotics, Human-Robot Interaction, and bio-inspired cognitive architectures. The module also covers scientific research methods and data analysis.

    • COMP5008 Advanced Machine Learning

      This module equips students with knowledge of the underlying theory of machine learning, as well as practical skills that enable them to apply theory to real-world problems. A variety of problems (including unsupervised, supervised and reinforcement learning tasks) are considered with a range of cutting-edge techniques. Students can customise the module to their career aims by identifying and exploring relevant data sets.

    • COMP5009 Computational Intelligence

      This module examines the state-of-the-art in computational intelligence, focussing on evolutionary computation, swarm intelligence, fuzzy systems and Bayesian and Markov networks. Students will learn about the underlying theory behind these techniques and gain practical experience of implementing them. CI approaches will be discussed against the backdrop of various industrial problems that they are suited to solving.

    • COMP5010 Topics in Applied Artificial Intelligence

      This module provides students with a view of how artificial intelligence is used within research and commercial settings. Delivered by a mix of academics developing novel AI techniques, and research and commercial users of AI, the module will enable students to appreciate the range of complexities inherent in the application of AI to solving real-world problems. As well as technical topics, the ethics of AI are explored.

    • MATH513 Big Data and Social Network Visualization

      Sophisticated analytics techniques are needed to visualize today's increasing quantities of Big Data. Up-to-date R tools including dplyr for data manipulation, ggplot2 for visualization, and knitr/LaTeX for document presentation are studied. These are applied to database interrogation, social network visualization and sentiment analysis. The module provides considerable experience of writing professionally documented R code using RStudio.

    • PROJ518 MSc Dissertation and Research Skills

      You will develop a methodical approach to research that helps propose research projects that are practically realistic and academically worthwhile. A substantial project will be planned and carried out using ethically suitable quantitative and qualitative research methods. The project will be reported through a high quality, scholarly and professional write-up, either as a formal dissertation or journal paper.

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

The following programme specification represents the latest programme structure and may be subject to change:

MSc Artificial Intelligence Programme Specification 7045

The modules shown for this course or programme are those being studied by current students, or expected new modules. Modules are subject to change depending on year of entry.

Entry requirements

A lower second class (2:2) honours degree or better in a STEM-based discipline. Applicants will need to have a sound awareness of programming and be comfortable in learning programming techniques. Applicants without any prior programming experience may be accepted subject to undertaking preparatory work prior to the start of the programme. Applicants with a lower classification, or substantial industrial experience in lieu of formal qualifications may be considered subject to interview.

A minimum IELTS English proficiency score of 6.5, with at least 5.5 in each component. 

The programme adheres to the University regulations and guidelines for the Accreditation of Prior Experiential Learning (APEL) and Accreditation of Prior Certificated Learning (APCL) for Masters programmes. 

Students are required to produce evidence of English language ability. This will normally be the equivalent of GCSE Grade C or above in English language or IELTS average score of 6.5 or above with at least 6.0 in the written component.

Fees, costs and funding

The UK is no longer part of the European Union. EU applicants should refer to our Brexit information to understand the implications.

New Student 2021 2022
Home £9,100 To be confirmed
International £16,200 To be confirmed
Part time (Home) To be confirmed To be confirmed
Full time fees shown are per annum. Part time fees shown are per a number of credits. Please note that fees are reviewed on an annual basis. Fees and the conditions that apply to them shown in the prospectus are correct at the time of going to print. Fees shown on the web are the most up to date but are still subject to change in exceptional circumstances. For more information about fees and funding please visit www.plymouth.ac.uk/money.

Alumnus loyalty reward for postgraduate study

The University applies a discretionary alumnus reward where alumni meet certain criteria on particular postgraduate taught courses.

  • A 20 per cent discount on home tuition fees.
  • Or a £2,000 discount on international tuition fees.
  • A 10 per cent alumni discount is available on the following programmes: MSc Advanced Psychology, MSc Clinical Psychology, MSc/PgDip Psychology and MSc Occupational Therapy.

For further details, programme exclusions and contact information, please see our alumnus discount policy.

Postgraduate scholarships for international students

We offer several scholarships for international students who wish to study postgraduate taught (PGT) degree programmes.

Find out about the postgraduate scholarships available to you as an international student

How to apply

When to apply

Most of our taught programmes begin in September. Applications can usually be made throughout the year, and are considered until programmes are full. 

Before you apply

Familiarise yourself with the information required to complete your application form. You will usually be required to supply:
  • evidence of qualifications (degree certificates or transcripts), with translations if not in English, to show that you meet, or expect to meet the entry requirements
  • evidence of English language proficiency, if English is not your first language
  • a personal statement of approximately 250-400 words about the reasons for your interest in the course and outlining the nature of previous and current related experience. You can write this into the online application form, or include it as a separate document
  • your curriculum vitae or résumé, including details of relevant professional/voluntary experience, professional registration/s and visa status for overseas workers
  • proof of sponsorship, if applicable.
If you require further information take a look at our application guidance.

Disability services

If you have a disability and would like further information about the support provided by University of Plymouth, please visit our Disability Services website. 

International students

Support is also available to overseas students applying to the University from our International Office via our how to apply webpage or email admissions@plymouth.ac.uk.

Submitting an application

Once you are happy that you have all of the information required you can apply using our online postgraduate application form (the blue 'Apply now' icon on this page).

What happens after I apply?

You will normally receive a decision on your application within four weeks of us receiving your application. You may be asked to provide additional information; two academic/professional references, confirming your suitability for the course; or to take part in an interview (which in the case of overseas students may be by telephone or video conference) and you will be sent a decision by letter or email.

We aim to make the application procedure as simple and efficient as possible. Our Admissions and Course Enquiries team is on hand to offer help and can put you in touch with the appropriate faculty if you wish to discuss any programme in detail.

If you would like any further information please contact the Admissions and Course Enquiries team:

Telephone: +44 (0)1752 585858
Email: admissions@plymouth.ac.uk 

Admissions policy

More information and advice for applicants can be referenced by downloading our Student Admissions Policy Prospective students are advised to read the policy before making an application to the University.

People

Research - Centre for Robotics and Neural Systems (CRNS)

The centre builds on world-leading excellence in computer science, robotics and neural systems research. Staff at the centre coordinate large projects and collaborate with major international centres in cognitive robotics and computational neuroscience.

Centre for Robotics and Neural Systems (CRNS)