Computer Vision, Robotics and Machine Learning MSc

Why choose this course

If you’re intrigued by artificial intelligence, creating machines that can ‘see’, and the application of artificial intelligence to robotics then this Masters is for you. The programme is offered by Surrey’s Centre for Vision, Speech and Signal Processing, which is recognised for its world-leading research in computer vision, multimedia signal processing and machine learning.

What you will study

Our MSc in Computer Vision, Robotics and Machine Learning provides in-depth training for students interested in a career in research-oriented institutions, or in industry, in cutting-edge technology companies focused on deep and machine learning, robotics and automation, and image and video analysis.

This Masters programme covers state-of-the-art computer vision and machine learning approaches for image and video analysis, as well as low-level image processing methods. Students also have the opportunity to substantially expand their programming skills through the projects they undertake.

Course facts

Qualification Study mode Course length Placement Start date
MSc Full-time 12 months October 2018
MSc Part-time 60 months October 2018

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

To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.

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 Centre for Vision, Speech and Signal Processing (CVSSP).

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
  • A number of our academics offer MSc projects in collaboration with our industrial partners

Research

The Department's Centre for Vision, Speech and Signal Processing is world-leading, with over 120 researchers working in the fields of deep learning, computer vision, signal processing and robotics. Their cutting edge 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.

Graduate prospects

We link with high tech 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.

Programme leader

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.

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 more.

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

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.

This course is subject to validation therefore no modules have been confirmed at this moment in time. These modules will appear once the course has been validated.

Timetable

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.

Entry requirements

A minimum 2:2 in a UK honours degree (or overseas equivalent) in Electrical or Electronic Engineering, Computer Science, Maths, Physics or a related discipline. Relevant industrial experience may also be considered.

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.

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 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.

Fees

Study mode Start date Placement UK/EU fees Overseas fees
Full-time October 2018 £9,800 £20,500
Part-time October 2018 £1,100* £2,300*
* per 15 credits

Please note:

  • These fees apply to students commencing study in the academic year 2018-19 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 part-time masters programme (excluding modular/self-paced/distance learning), the annual fee is payable in Year 1 and Year 2 of the programme.

View the list of fees for all postgraduate taught programmes.

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.

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