MSc Computer Vision, Robotics and Machine Learning

Postgraduate Online events on 26th April, 17th May and 22nd May.

Why Choose This Course

If you’ re intrigued by artificial intelligence, the application of robotics, and creating machines that can ‘see’, then this master's course 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.

In 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&rsquo'll also have the opportunity to substantially expand your programming skills through the projects you choose to take on.

Industrial Collaborations

We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. We have collaborated with industrial partners such as the BBC, Foundry, LionHead and BAE on research and technology transfer projects.

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 (IET) on behalf of the Engineering Council for the purposes of fully meeting the academic requirement for registration as an Incorporated Engineer and partially meeting the academic requirement for registration as a Chartered Engineer.

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 programs based on a 15-credit tariff. Modules can be either 15, 30, 45, 75, or 120 credits, and additionally for some masters dissertations, 90 credits.

The structure of our programs follows clear educational aims that are tailored to each program. These are all outlined in the program specifications which include further details such as the learning outcomes

Year 1 Full-time

• Computer Vision and Pattern Recognition
• Fundamentals of Digital Signal Processing
• Internet of Things
• Satellite Remote Sensing
• Speech & Audio Processing & Recognition
• Advanced Topics in Computer Vision and Deep Learning
• AI and AI Programming
• Applied Machine Learning
• Robotics
• 60 Credit Standard Project

Optional modules for Year 1 (full-time) - FHEQ Levels 6 and 7

Four optional modules in Semester 1 are 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

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.

We have links with innovative companies in machine learning, computer vision, and gaming, including Amazon, Microsoft, and Sony. We also have links with the broader industry, where skills such as deep learning are in great demand.

97 percent of our electrical and electronic engineering postgraduate taught students go on to employment or further study (Graduate Outcomes 2023, HESA).