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Artificial Intelligence

MSc or PGDip or PGCert

Key facts

Start dates

September 2023 / September 2024



Course length

Full time: Full time: MSc - 1 year (12 months); PG Dip - 6 months; PG Cert - 3 months

Part time: Part time: MSc - 2 years (24 months); PG Dip - 18 months (12 months study time); PG Cert - 6 months


Our Artificial Intelligence (AI) course allows you to develop the skills, knowledge and understanding to:

  • pursue careers in the cutting edge of AI
  • implement novel technological solutions in real world problems.

It is ideal for recent graduates in computing, mathematics, engineering or a science-related subject with good programming skills. And those with substantial experience in the computing industry who want to gain a qualification that develops their expertise.

The course is informed by the state-of-the-art research being undertaken in the school. You will study:

  • machine learning
  • deep learning
  • data science
  • data visualisation
  • big data and the cloud
  • intelligent autonomous systems
  • fundamental relevant aspects of cybersecurity.

Our labs are equipped with industry-standard equipment and software tools. This includes a ‘Fab’ lab and robotics lab with a range of platforms for you to implement Artificial Intelligence algorithms.

AI project skeleton head

How to apply

Entry requirements

Specific entry requirements

Due to great interest in this course for September 2023 entry, the deadline to receive applications is Wednesday 22 March 2023 for all applicants who will require a visa to study in the UK. As long as we receive your application on or before 22 March 2023 it will be given full consideration. Those not requiring a visa to study in the UK can continue to apply beyond 22 March 2023. 

A degree equivalent to at least a British lower second class bachelor's (2:2) in computing, maths, engineering or a science-related subject, in which good programming skills have been developed. Those whose first degree is not in these areas, but who have worked in a related industry, and have good relevant experience and programming skills, can also apply.

If you have no experience or degree in a computing related discipline you should consider our MSc in Computing Science.

For the Postgraduate Certificate Research Project you should provide evidence of experience in research and study methods.

Please also see the University's general entry requirements.

English language requirements

If your first language is not English you will require a minimum IELTS score of 6.0 with 6.0 in all components.


An equivalent English language qualification acceptable to the University.

Please also see the University's standard English language requirements.

International qualifications and equivalences


English requirements for visas

If you need a student visa to enter the UK you will need to meet the UK Visas and Immigration minimum language requirements as well as the University's requirements. Find out more about English language requirements.

Pathways courses for international and EU students

We offer a range of courses to help you meet the entry requirements for your postgraduate course and also familiarise you with university life in the UK.

Take a Pre-Master's course to develop your subject knowledge, study skills and academic language level in preparation for your master's course.

If you need to improve your English language, we offer pre-sessional English language courses to help you meet the English language requirements of your chosen master’s course.

Terms and Conditions of Enrolment

When you accept our offer, you agree to the Terms and Conditions of Enrolment. You should therefore read those conditions before accepting the offer.

Application process

Tuition fees

Please see the fees note
Home (UK) full time
Masters £8,350; Diploma £7,350; Certificate £4,175

Home (UK) part time

International full time

Home (UK) full time
Masters £8,700; Diploma £7,700; Certificate £4,350

Home (UK) part time

International full time

Questions about fees?

Contact Student Finance on:

Tuition fees

2022 / 23
Home (UK) full time
Masters £8,350; Diploma £7,350; Certificate £4,175

Home (UK) part time

International full time

2023 / 24
Home (UK) full time
Masters £8,700; Diploma £7,700; Certificate £4,350

Home (UK) part time

International full time

Questions about fees?

Contact Student Finance on:

+44 (0)1865 483088

Fees quoted are for the first year only. If you are studying a course that lasts longer than one year, your fees will increase each year.

Additional costs

Please be aware that some courses will involve some additional costs that are not covered by your fees. Specific additional costs for this course are detailed below.

Funding your studies

Financial support and scholarships

Featured funding opportunities available for this course.

The Department of Computing and Communication Technologies awards a limited number of scholarships for its taught postgraduate programmes, which are awarded on a competitive basis to UK, EU and international postgraduates each year. 

All financial support and scholarships

View all funding opportunities for this course

Learning and assessment

You need to gain credits depending on the level of award you are studying:

MSc in Artificial Intelligence
You need 180 credits including:

  • 120 credits from taught modules
  • 60 credits from your dissertation.

Postgraduate Diploma in Artificial Intelligence
You must achieve 120 taught module credits.

In some cases, it may be possible for you to gain 60 taught module credits and 60 credits from a dissertation).

Postgraduate Certificate in Artificial Intelligence
You must achieve 60 credits.

You can also do a Postgraduate Certificate in Artificial Intelligence Research Project.

Part-time students normally distribute the work evenly over two years.

Student building AI project with a screwdriver

Study modules

The modules listed below are for the master's award. For the PGDip and PGCert awards your module choices may be different. Please contact us for more details.

Taught modules

Compulsory modules

Introduction to Machine Learning (10 credits)

This module studies the fundamentals of machine learning methodologies, implementations and analysis methods appropriate for machine learning applications. Compulsory for MSc and PG Dip.

Foundations of Artificial Intelligence (AI) (10 credits)

This module teaches the fundamental concepts of AI including classical and modern approaches to AI and the philosophical bases of AI. Compulsory for MSc and PG Dip.

Autonomous Intelligent Systems (20 credits)

This module equips you with the knowledge and critical understanding how Autonomous Intelligent Systems are employed in a wide range of environments with different functionalities. Compulsory for MSc.

AI Systems Engineering (20 credits)

This module provides students with skills to critically evaluate and analyse the application artificial intelligence in the domain of systems engineering. Compulsory for MSc.

Data Visualisation (10 credits)

This module covers state of the art tools and techniques to build useful visualisations for different types of data sets and application scenarios. Compulsory for MSc.

Big Data and the Cloud (20 credits)

The cloud has become a key part of modern life and with it comes vast amounts of data. This module looks at how clouds work and can be used to tackle the big data challenges of modern science and business. Compulsory for MSc.

Research, Scholarship and Professional Skills (20 credits)

Advanced Machine Learning (10 credits)

This module equips students with skills to critically evaluate complex machine learning algorithms in different application scenarios. Compulsory for MSc.

Final project

Compulsory modules

Dissertation in Computing Subjects (60 credits)

This is an individual research and development project that allows you to study a topic of your choice in the area of Artificial Intelligence in depth, guided by your supervisor. The work may be undertaken in close cooperation with a research, industrial or commercial organisation. You undertake your dissertation over the summer period if you are a full time student.

independent Study II (20 credits)

Please note: As our courses are reviewed regularly as part of our quality assurance framework, the modules you can choose from may vary from those shown here. The structure of the course may also mean some modules are not available to you.

Learning and teaching

You will be taught with a combination of lectures and practical sessions. Lectures provide a theoretical basis, while practical sessions strengthen your understanding with active involvement.

You will be provided with a varied experience, as well as the opportunity to discuss your work directly with lecturers.

Many of the modules are enriched by the teaching staff's research expertise. We also invite visiting lecturers from research organisations and industry to come and give guest lectures.


Assessment methods used on this course

Assessment is continuous and includes:

  • coursework exercises
  • presentations
  • lab work
  • examinations
  • reports.


The School of Engineering, Computing and Mathematics is home to world-leading and award-winning research. Our focus is on user-inspired original research with real-world applications.

We have a vibrant and growing research community, with a wide range of activities from model-driven system design and empirical software engineering through to web technologies, cloud computing and big data, digital forensics and computer vision.

Staff and students collaborate on projects supported by the EPSRC, the EU, the DTI, and several major UK companies.

Computing achieved an excellent assessment of its UoA (Unit of Assessment) 11 return for REF 2014 (Research Excellence Framework).

Students on this course can be involved with research in the following research groups:

After you graduate

Career prospects

We focus on using industry standard tools to solve practical and industrially relevant problems, and using those problems to teach the theoretical concepts. This ensures that students have the opportunity to acquire skills which will not just equip them for today's computing industry, but for a lifelong career in the computing industry.


Graduates, from the programme, will be ideally equipped for a career in wide variety of industries. Graduates are employed across a whole range of jobs, including 

  • data scientist
  • software data engineer
  • machine learning engineer
  • machine learning scientist
  • AI architect
  • AI consultant
  • AI specialist
  • ML architect
  • knowledge engineer.

Programme changes:
On rare occasions we may need to make changes to our course programmes after they have been published on the website. For more information, please visit our changes to programmes page.