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Artificial Intelligence (MSc)

Explore the techniques and applications of artificial intelligence (AI) and develop your practical skills through exposure to real-world problems and datasets.

Learn the ethical and social impacts of AI technologies while developing your critical judgement, intellectual integrity and practical skills on client-facing projects.

This unique course provides specialist knowledge in areas such as automated reasoning, knowledge representation and machine learning. You also have the opportunity to customise your learning experience to suit your interests and career aspirations by choosing from a range of optional modules, professional work placements and projects.

High-performing graduates from this programme will be well-prepared for commencing a research career in AI.

This one-year degree falls under the umbrella of the Data Science Academy (DSA), run by the School of Computer Science and Informatics, in partnership with the School of Mathematics. You will benefit from the shared knowledge and skills of both Schools. However, your degree will still be run by the School of Computer Science & Informatics. 

Distinctive features

  • This course incorporates project-based learning using real-world datasets and problems.
  • You will have the opportunity to gain valuable work experience in professional work placements and projects with leading AI practitioners.
  • Some of your modules will be taught in our newly-renovated Turing Suite.
  • You will be provided with a laptop during induction week that will remain with you throughout the duration of the course.
  • This course is informed by the most up-to-date research and co-designed by world-renowned AI researchers from the Knowledge and Reasoning Priority Area.
  • You will be provided with a laptop during induction week that will remain with you throughout the duration of the course.

Key facts

Next intakeSeptember 2020
Duration1 year

Admissions criteria

We welcome applications from computer literate graduates who have a good honours degree, or equivalent professional qualification in a subject such as Computer Science or a related subject.

Applicants will possess a 2:1 honours degree in Computer Science, Computing or a cognate subject. Applicants with a 2:2 honours degree in computer science, computing or a cognate subject may be invited to participate in a telephone or remote interview.

If your first language is not English you must provide evidence of competence in English. Our standard requirement is an overall IELTS score of 6.5 with no area less than 5.5.  The University offers English language courses that can help you achieve this.

Please feel free to supplement your application with a detailed CV or any other supporting material you may consider to be appropriate.

Programmes start in September each year but applications are considered as they arrive throughout the year.

You apply directly to the University online for a postgraduate taught course

Find out more about English language requirements.

Applicants who require a Tier 4 visa to study in the UK must present an acceptable English language qualification in order to meet UKVI (UK Visas and Immigration) requirements

This is a two-stage programme taught over one year for a total of 180 credits. The taught stage is 120 credits, followed by a 60-credit research project. All modules in the taught stage are worth 20 credits.

The Master’s stage of your degree will be an individual project (worth 60 credits) which you will write up as a dissertation, after the Diploma stage. This project will be carried out the summer under the supervision of a member of academic staff.

The modules shown are an example of the typical curriculum and will be reviewed prior to the 2020/21 academic year. The final modules will be published by September 2020.

You will study four 20-credit compulsory modules to a total of 80 credits, and choose a further 40 credits from a list of carefully selected optional modules. This will be followed by a 60-credit dissertation project undertaken in the summer

The University is committed to providing a wide range of module options where possible, but please be aware that whilst every effort is made to offer choice this may be limited in certain circumstances. This is due to the fact that some modules have limited numbers of places available, which are allocated on a first-come, first-served basis, while others have minimum student numbers required before they will run, to ensure that an appropriate quality of education can be delivered; some modules require students to have already taken particular subjects, and others are core or required on the programme you are taking. Modules may also be limited due to timetable clashes, and although the University works to minimise disruption to choice, we advise you to seek advice from the relevant School on the module choices available.

How will I be taught?

The School of Computer Science and Informatics has a strong and active research culture which informs and directs our teaching. We are committed to providing teaching of the highest standard.

A diverse range of teaching and learning styles are used throughout the MSc Artificial Intelligence. Modules are delivered through a series of either full- or half-day contact sessions, which include lectures, seminars, workshops, tutorials and laboratory classes.

Most of your taught modules will have further information for you to study and you will be expected to work through this in your own time according to the guidance provided by the lecturer for that module.

You will also undertake a project and independent study to enable you to complete your dissertation. Dissertation topics may be suggested by yourself or chosen from a list of options proposed by academic staff and industrial partners, reflecting their current interests.

How will I be supported?

We pride ourselves on providing a supportive environment in which we are able to help and encourage our students.

At the start of your course you will be allocated a Personal Tutor who is an academic member of staff in the School and serves as a point of contact to advise on both academic and personal matters in an informal and confidential manner. Your Personal Tutor will monitor your progress throughout your time at university and will support you in your Personal Development Planning.

Outside of scheduled tutor sessions, our Senior Personal Tutor runs an open-door policy, being on hand to advise and respond to any personal matters as they arise.

How will I be assessed?

The taught modules within the programme are assessed through examinations and a wide range of in-course assessments, such as:

Written reports; Extended essays; Practical assignments; Oral presentations.

Feedback on coursework may be provided via written comments on work submitted, by provision of ‘model’ answers and/or through discussion in contact sessions.

The individual project and dissertation enables students to demonstrate their ability to build upon and exploit knowledge and skills gained in earlier stages of the Programme. Furthermore it provides the opportunity for students to exhibit critical and original thinking based on a period of independent study and learning.

What skills will I practise and develop?

Knowledge & Understanding:

On successful completion of the Programme you will be able to demonstrate:

  • Understanding of the importance of how data is represented for the success of artificial intelligence methods
  • Knowledge of the key concepts and algorithms underlying artificial intelligence methods
  • Understanding of the theoretical properties of different artificial intelligence methods
  • Insight and foresight of how artificial intelligence methods influence the success of a given task

Intellectual Skills:

On successful completion of the Programme you will be able to demonstrate:

  • An ability to implement and evaluate artificial intelligence methods to solve a given task
  • An ability to explain and communicate the basic principles underlying common artificial intelligence methods
  • Critical appraisal of the ethical implications and societal risks associated with the deployment of artificial intelligence methods

Professional Practical Skills:

On successful completion of the Programme you will be able to demonstrate:

  • Capacity to formalize real-world problems in relation to chosen artificial intelligence methods
  • Ability to choose an appropriate artificial intelligence method (and data pre-processing strategy if needed) to address the needs of a given application setting
  • Competence in implementing artificial intelligence methods, taking advantage of existing libraries where appropriate

Transferable/Key Skills:

On successful completion of the Programme you will be able to demonstrate:

  • Critical appraisal of your own and other’s work through written and verbal means
  • Clear and efficient communication of complex ideas, principles and theories by oral, written and practical means, to a range of audiences
  • Appreciation of opportunities for career development
  • An ability to undertake independent study and critical reflection

Graduates from this programme will be ideally placed to develop careers as data scientists, artificial intelligence engineers, and data engineers.

Tuition fees

UK and EU students (2020/21)

Tuition feeDepositNotes

More information about tuition fees and deposits, including for part-time and continuing students.

EU students entering in 2019/20 will pay the same tuition fee as UK students for the duration of their course. Please be aware that fees may increase annually in line with inflation. No decisions regarding fees and loans for EU students starting in 2020/21 have been made yet. These will be determined as part of the UK's discussions on its membership of the EU and we will provide further details as soon as we can.

Students from outside the EU (2020/21)

Tuition feeDepositNotes

More information about tuition fees and deposits, including for part-time and continuing students.

Will I need any specific equipment to study this course/programme?


Industrial partners are invited to support the delivery of a variety of modules by providing real data and problems to be addressed as part of coursework examination.