Computer Vision, Robotics and Machine Learning MSc – 2023 entry
Key information
Start date: September 2023
- Study mode and duration
- Full-time: 1 year (maximum course length)*
- Part-time: 5 years (maximum course length)*
Why choose this course
If you’re intrigued by artificial intelligence (AI), the application of robotics and creating machines that can ‘see’, then our MSc is for you.
This course is taught by academics from our Centre for Vision, Speech and Signal Processing (CVSSP), which is internationally recognised for its research in computer vision, multimedia signal processing and machine learning. With a diverse community of more than 120 researchers, CVSSP is one of the largest and most respected vision research groups in the UK.
What you will study
Our MSc will provide you with in-depth training and hands-on learning experiences. It’s 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’ll explore advanced computer vision and machine learning approaches for image and video analysis, as well as low-level image processing methods.
You’ll also have the opportunity to substantially expand your programming skills through the projects you choose to take on.
Please be aware: the course content and modules listed for this course are subject to change for the 2023/24 academic year, whilst we undertake a curriculum design review. Please contact the programme leader if you have any queries about the course.
Facilities, equipment and support
Several modules on our course are supported by laboratory classes. Here, you’ll gain hands-on experience in artificial intelligence programming and develop practical skills in the design of robotic devices.
We’ll provide you with computing support for any specialised software (e.g. MATLAB) required during the course. The faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a 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 our Centre for Vision, Speech and Signal Processing.
Industrial collaborations
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
- Several of our academics offer MSc projects in collaboration with our industrial partners.
Research
Our Centre for Vision, Speech and Signal Processing is internationally renowned, with more than 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 is inspired by our Surrey Space Centre, building on our specialisms in space robotics.
Professional recognition
MSc - Institution of Engineering and Technology (IET)
Accredited by the Institution of Engineering and Technology on behalf of the Engineering Council for the purposes of fully meeting the academic requirement for registration as a Chartered Engineer.
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. Our graduates have lifetime access to Surrey Pathfinder, our online portal for appointment and events bookings, jobs, placements and interactive development tools.
We have links with innovative companies in machine learning, computer vision and gaming. These include Sony, Microsoft and the broader industry, where skills such as deep learning are in great demand.
93 per cent of our electrical and electronic engineering postgraduate students go on to employment or further study (Graduate Outcomes survey 2022, HESA).
Academic year structure
If you’re studying this course full-time, you’ll study eight modules across the year – four in each semester. You will work on your project full time during the summer period for approximately two and a half months, whilst prior to that during semester time you will work on the initial stages of the project part time and complete an interim report. This means that if you begin your course in February, you will complete your project in between the two semesters, while if you begin your course in September, you will complete your project after the two semesters.
You can also study this MSc 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
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, 75 and 120 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:
Optional modules for Year 1 (full-time) - FHEQ Levels 6 and 7
Four optional modules in Semester 1 to be selected but only one level 6 module EEE3008 OR EEE3032 can be selected
No optional modules in Semester 2
No more than two modules at FHEQ level 6 may be selected in the whole year
Optional modules for Unstructured (3-5 years) - FHEQ Levels 6 and 7
Four optional modules in Semester 1 to be selected but only one level 6 module EEE3008 OR EEE3032 can be selected
No optional modules in Semester 2
No more than two modules at FHEQ level 6 may be selected in the whole year
Timetable
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 Academic Hive. View our Code of practice for the scheduling of teaching and assessment (PDF).
Contact hours
Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.
Entry requirements
A minimum of a 2:2 UK honours degree in 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.
Do I meet the requirements for this course?
We require you to submit a full application so that we can formally assess whether you meet the criteria published. Unfortunately, we are unable to provide an outcome based on an enquiry (via email, webform enquiry, phone or live chat).
International entry requirements by country
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.
Credit transfer
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 your experience exceeds the typical requirements for entry to the programme, 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. If you can demonstrate that you have met the learning outcomes for specific modules through your previous learning, it may be possible to exempt you from those modules, and for you to 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.
In some cases, prior knowledge and skills may allow applicants to join the start of a course without meeting the formal entry requirements.
Please see our code transfer and recognition of prior learning guide (PDF) and recognition of prior learning and prior credit web page for further information. Please email Admissions (admissions@surrey.ac.uk) with any queries.
Fees per year
Start date: September 2023
Full-time - 1 year
- UK
- £10,900
- Overseas
- £24,400
Part-time - 5 years
- UK
- £1,200
- Overseas
- £2,700
Please note:
- These fees apply to students commencing study in the academic year 2023-24 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 2023-24 academic year
- Annual fees will increase by 4% for each subsequent year of study, rounded up to the nearest £100, subject to any overriding applicable legislative requirements.
Payment schedule
- Students in receipt of a tuition fee loan: Will have their fees paid by the Student Loans Company in line with their schedule
- International students, or UK/EU students who have not taken out a tuition fee loan: Are required to pay their fees either in full at the beginning of the programme or in two instalments as follows:
- 50% payable 10 days after the invoice date (expected to be early October of each academic year)
- 50% in January of the same academic year.
The exact date(s) will be detailed on invoices. Students on certain part-time programmes, where fees are paid on a modular or stage basis, are not eligible to pay their fees by instalment.
- If you are sponsored: You will provide us with valid sponsorship information that covers the period of your study.
Additional costs
There are associated costs with this course:
- Books/stationery/admin: Costs may be incurred associated with the purchase of writing paper and associated stationery.
Funding
You may be able to borrow money to help pay your tuition fees and support you with your living costs. Find out more about postgraduate student finance.
Scholarships and bursaries
We're committed to making sure that we offer support for students who might need it.
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Course | Status |
|---|---|
Computer Vision, Robotics and Machine Learning MSc Full-time, 12 months, September 2023 | Applications open Closing date: Thursday 1 June 2023 |
Please note that we may have to close applications before the stated deadline if we receive a high volume of suitable applications. We advise you to submit your application as soon as it is ready. | |
Computer Vision, Robotics and Machine Learning MSc Part-time, 60 months, September 2023 | Applications open Closing date: Thursday 1 June 2023 |
Please note that we may have to close applications before the stated deadline if we receive a high volume of suitable applications. We advise you to submit your application as soon as it is ready. | |
Admission information
Our postgraduate admissions policy* provides the basis for admissions practice across the University and gives a framework for how we encourage, consider applications and admit students. You can also read our postgraduate applicant guidance.
Terms and conditions
When you accept an offer of a place at the University of Surrey, you are agreeing to comply with our Charter, Statutes, Ordinances, Policies, 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 registration terms and conditions (PDF) for the 2022/2023 academic year as a guide as to what to expect.
Please note: the offer terms and conditions and registration terms and conditions which you will be asked to agree to may be different from those detailed in the examples. Our offer terms and conditions will generally 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 be available at the start of each academic year and will vary to take into account specifics of your course and changes for the specific academic year.
Disclaimer
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 our full disclaimer.
Course location and contact details
Campus location
Stag HillStag Hill is the University's main campus and where the majority of our courses are taught.
University of Surrey Admissions
- Phone: +44 (0)1483 682222
Address
University of Surrey
Guildford
Surrey GU2 7XH