The MSc in Artificial Intelligence has a modular course-unit design providing you with maximum flexibility and choice. To qualify for a master’s degree, you must pass modules amounting to 180 credits. This comprises 120 credits taught modules plus your dissertation (60 credits).
The MSc in Artificial Intelligence with placement enables you to work in industry for a year in the middle of your course to give valuable workplace experience. Placements are not guaranteed, but the School's dedicated placement team will help with the process of finding and applying for placements. To qualify for a master’s degree with placement, you must pass modules amounting to 180 credits plus the zero-credit placement module. This comprises 120 credits taught modules plus your dissertation (60 credits).
The Postgraduate Diploma in Artificial Intelligence allows you to concentrate on the taught part of the degree and is ideal for people working in the computing industry who wish to update their skills. To qualify for a Postgraduate Diploma, you must pass modules amounting to 120 taught credits. In some cases, it may be possible for a student on a Postgraduate Diploma to do 60 taught modules credits plus your dissertation (60 credits).
The Postgraduate Certificate in Artificial Intelligence allows you to concentrate on the taught part of the degree and is ideal for people working in the computing industry who wish to learn a specific area in this rapidly changing discipline. To qualify for a Postgraduate Certificate, you must pass modules amounting to 60 credits.
You can also do a Postgraduate Certificate in Artificial Intelligence Research Project.
Part-time students normally distribute the work evenly over a two-year period.
You will be studying the following modules:
- Autonomous Intelligent Systems (compulsory for MSc) equips you with the knowledge and critical understanding how Autonomous Intelligent Systems are employed in a wide range of environments with different functionalities.
- Introduction to Machine Learning (compulsory for MSc and PG Dip) studies the fundamentals of machine learning methodologies, implementations and analysis methods appropriate for machine learning applications.
- Foundations of Artificial Intelligence (AI) (compulsory for MSc and PG Dip) teaches the fundamental concepts of AI including classical and modern approaches to AI and the philosophical bases of AI.
- Cyber Security and the Web (compulsory for MSc) equips students with the conceptual understanding, and practical skills, necessary to develop interactive, human computer interfaces, using a variety of web technologies, and to evaluate alternative designs, and to be able to critically analyse and evaluate the security of web sites and web applications.
You will be studying the following modules:
- Data Visualisation (compulsory for MSc) covers state of the art tools and techniques to build useful visualisations for different types of data sets and application scenarios.
- Big Data and the Cloud (compulsory for MSc) 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.
- Advanced Machine Learning (compulsory for MSc) equips students with skills to critically evaluate complex machine learning algorithms in different application scenarios.
- Artificial Intelligence Systems Engineering (compulsory for MSc) provides students with skills to critically evaluate and analyse the application artificial intelligence in the domain of systems engineering.
As courses are reviewed regularly as part of our quality assurance framework, modules offered may differ from those listed.
Students undertaking an MSc with placement will do a 1-year placement in industry. The placement will be undertaken after the taught component and before doing the dissertation.
Students studying for an MSc will also take:
- MSc Dissertation which 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.
Teaching and learning
Lectures provide a theoretical basis, while the practical sessions are used to strengthen your understanding by active involvement. Coursework and projects form the basis for continuous assessment. These methods have been developed to provide the varied experience that our students require, including the opportunity to discuss your work directly with the lecturers.
Many of the modules are enriched by the teaching staff's research expertise. There are also visiting lecturers from research organisations and industry.
Approach to assessment
Assessments include coursework exercises, presentations, lab work, examinations and reports.
Based on your own dedicated campus our labs are equipped with industry-standard equipment and software tools. This enables you to develop skills of immediate relevance to industry needs while also providing a sound practical basis that enhances you understanding of theoretical concepts. There is a ‘Fab’ lab and robotics lab which offer a range of platforms on which to implement Artificial Intelligence algorithms.
Students on placement are responsible for living costs associated with their placement.
Part time study is an option on this programme for students who wish to combine their study with work. Where possible we try to ensure that part time students only need to attend for 1 day a week, although students will be expected to undertake additional independent study.
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