Computer Vision, Robotics and Machine Learning MSc
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 who is interested in a career in research-oriented institutions or pioneering technology companies which focus on deep and machine learning, robotics and automation and image and video analysis.
On this course, you will cover 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 take on.
|Qualification||Study mode||Course length||Placement||Start date|
|MSc||Part-time||60 months||October 2019|
|MSc||Full-time||12 months||October 2019|
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.
Facilities, equipment and support
A number of the modules on our course, where appropriate, 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 programme, 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 the CVSSP.
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 in our specialisms of space robotics.
We link with innovative firms in machine learning, computer vision and gaming including Sony, Microsoft and the broader industry, where skills such as deep learning are in great demand.
COLLOMOSSE JP Dr (Elec Elec En)
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 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.
Postgraduate open afternoon
Visit the University to find out more about studying here
Join a webinar and speak to our current students
“I’ll soon be starting a PhD at Surrey – I’m confident that the Masters course has improved my abilities to perform research, as well as increasing my critical thinking and problem solving skills.”
MSc Computer Vision, Robotics and Machine Learning
The lecturers are fantastic. Not only are they knowledgeable in their own fields, they are also very good at communicating in an easy-to-understand way.
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 two semesters you will also apply for and agree a project with an academic supervisor and begin initial work on the project before working on it full time work 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.
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.
Modules listed are indicative, reflecting the information available at the time of publication. Please note that modules may be subject to teaching availability and/or student demand.
Year 1 (full-time)
Optional modules for Year 1 (full-time) - FHEQ Levels 6 and 7
A full-time student must choose:
TWO in Semester 1
ZERO in Semester 2
Unstructured (3-5 years)
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).
Learning and disability
We have two services, the Student Personal Learning and Study Hub (SPLASH) and Additional Learning Support (ALS) which can help develop your learning.
Student Personal Learning and Study Hub
SPLASH is a learning space in the Library where our learning development team is based. It comprises dedicated Student Learning Advisers and Information Skills Librarians who can help you develop your academic and research skills, including writing, presenting, revision and critical thinking.
Find out more about the study support available.
Additional Learning Support
ALS is the University’s disability and neurodiversity service which supports students with disabilities, long-term health conditions, specific learning differences (for example: dyslexia and dyspraxia) and other neurodiverse conditions (for example: autism spectrum and attention deficit disorder).
If you have a disability, we encourage you to disclose your condition and register with the service so you can be appropriately supported during your studies.
The ALS team can arrange exam and learning support adjustments, give advice on applications for the Disabled Students' Allowance and screen students for dyslexia and dyspraxia. Regular study skills and mentoring support is also available.
See the Additional Learning Support website for more information.
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.
View entry requirements by country
English language requirements
IELTS Academic: 6.5 overall, 6.0 in each component (or equivalent).
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 is also an IELTS test centre.
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.
|Study mode||Start date||Placement||UK/EU fees||Overseas fees|
- These fees apply to students commencing study in the academic year 2019-20 only. Fees for new starters are reviewed annually.
- If you are on a two-year full-time Euromasters or MFA programme, or a two-year or three-year part-time masters programme (excluding modular/self-paced/distance learning), the annual fee is payable in Year 1 and Year 2 of the programme.
Scholarships and bursaries
Surrey International Scholarship for Engineering and Physical Sciences 2019 entry
Find out more