Why choose this course
If you’re intrigued by artificial intelligence, the application of robotics, and creating machines that can ‘see’, then this masters course is for you.
Our MSc in Computer Vision, Robotics and Machine Learning is taught by academics from
our Centre for Vision, Speech and Signal Processing (CVSSP). The Centre is internationally recognised for its research in computer vision, multimedia signal processing and machine learning. With a diverse community of more than 120 researchers, they are one of the largest and best respected vision research groups in the UK.
What you will study
Our MSc in Computer Vision, Robotics and Machine Learning will provide you with in-depth training and hands-on learning experiences. It is well-suited to anyone interested in a career in research-oriented institutions or pioneering technology companies that specialise in deep and machine learning, robotics and automation, and image and video analysis.
On this course, you will explore advanced computer vision and machine learning approaches for image and video analysis, as well as low-level image processing methods. You will also have the opportunity to substantially expand your programming skills through the projects you choose to take on.
Facilities, equipment and support
A number of the modules on our course are supported by laboratory classes where you can gain hands-on experience in artificial intelligence programming and develop your practical skills in the design of robotic devices.
We provide computing support with any specialised software required during the course, for example MATLAB. The Faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices.
Specialist experimental and research facilities, for computationally-demanding projects or those requiring specialist equipment, are provided by Surrey’s Centre for Vision, Speech and Signal Processing.
We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. Our industrial collaborations include:
- Research and technology transfer projects with industrial partners such as the BBC, Foundry, LionHead and BAE
- A number of our academics offer MSc projects in collaboration with our industrial partners.
Our Department's Centre for Vision, Speech and Signal Processing is internationally renowned, with over 120 researchers working in the fields of deep learning, computer vision, signal processing and robotics. Their forward-thinking research is reflected in the course content, which is frequently updated with the latest developments. Uniquely, our robotics material integrates with Surrey Space Centre, building on our specialisms of space robotics.
Study and work abroad
There may be opportunities to acquire valuable European experience by working or conducting research abroad during your degree or shortly afterwards. It is possible to do this in the summer period with an Erasmus+ grant working on your dissertation or as a recent graduate. In order to qualify your Erasmus+ traineeship must be a minimum of two months.
Careers and graduate prospects
We offer careers information, advice and guidance to all students whilst studying with us, which is extended to our alumni for three years after leaving the University.
At Surrey, we have links with innovative companies in machine learning, computer vision and gaming including Sony, Microsoft and the broader industry, where skills such as deep learning are in great demand.
Academic year structure
If you’re studying this course full-time, you will study eight modules across the year – four in each semester. During the first semester, you will also apply for and agree on a project with an academic supervisor and begin initial work on the project before working on it full-time after the end of Semester 2. From that point, you will have approximately two and a half months to complete the work and write up your dissertation.
You can also study this course part-time, taking between two and five years. The length depends on how many modules you study each year. You can study between two and six modules each year. We recommend part-time students work on their project in their final year of study when all eight modules have either been completed or are near completion.
Modules listed are indicative, reflecting the information available at the time of publication. Please note that modules may be subject to teaching availability, student demand and/or class size caps.
The University operates a credit framework for all taught programmes based on a 15-credit tariff. Modules can be either 15, 30, 45 or 60 credits, and additionally for some masters dissertations, 90 credits.
The structure of our programmes follows clear educational aims that are tailored to each programme. These are all outlined in the programme specifications which include further details such as the learning outcomes:
Course timetables are normally available one month before the start of the semester. Please note that while we make every effort to ensure that timetables are as student-friendly as possible, scheduled teaching can take place on any day of the week (Monday–Friday). Wednesday afternoons are normally reserved for sports and cultural activities. Part-time classes are normally scheduled on one or two days per week, details of which can be obtained from the course administrators. View our Timetabling Policy (PDF).
A minimum of a 2:2 UK honours degree in either Computer Science, Electronic Engineering, Mathematics, or Physics, or a recognised equivalent international qualification. We'll also consider relevant degree subjects or significant relevant work experience if you don’t meet these requirements.
English language requirements
IELTS Academic: 6.5 overall with 6.0 in Writing and 5.5 in each other element.
View the other English language qualifications that we accept.
If you do not currently meet the level required for your programme, we offer intensive pre-sessional English language courses, designed to take you to the level of English ability and skill required for your studies here.
The University of Surrey recognises that many students enter their higher education course with valuable knowledge and skills developed through a range of professional, vocational and community contexts. If this applies to you, a process called recognition of prior learning (RPL) may allow you to enter your course at a point appropriate to your previous learning and experience, or to join the start of a course without the formal entry requirements. This means that you may be exempt from certain elements of study in the course for which you have applied and be awarded credit based on your previous qualifications/experience. There are restrictions on RPL for some courses and fees may be payable for certain claims.
Please see the code of practice for recognition of prior learning and prior credit: taught programmes (PDF) for further information. Please email Admissions with any queries.
- These fees apply to students commencing study in the academic year 2020-21 only. Fees for new starters are reviewed annually.
- If you are on an unstructured self-paced part-time course, the fee shown is per 15 credits for the 2020-21 academic year. The fee payable in subsequent years will be reviewed annually.
There are associated costs with this course:
- Books/stationery/admin: Costs may be incurred associated with the purchase of writing paper.
You may be able to borrow money to help pay your tuition fees and support you with your living costs. Find out more about student finance.
Scholarships and bursaries
We're committed to making sure that we offer support for students who might need it.
Asylum Seeker Bursary
Application Deadline: 30.06.20
Find out more
Terms and conditions
When you accept an offer of a place at the University of Surrey, you are agreeing to comply with our policies and regulations, and our terms and conditions. These terms and conditions are provided in two stages: first when we make an offer and second when students who have accepted their offers register to study at the University. View our offer terms and conditions and our generic registration terms and conditions (PDF) as a guide as to what to expect.
Please note: our offer terms and conditions will be available in the September of the calendar year prior to the year in which you begin your studies. Our registration terms and conditions will vary to take into account specifics of your course.
This online prospectus has been prepared and published in advance of the academic year to which it applies. The University of Surrey has used its reasonable efforts to ensure that the information is accurate at the time of publishing, but changes (for example to course content or additional costs) may occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for a course with us. Read more.