
Master of Science - Computer Vision, Robotics and Machine Learning
Stag Hill, University Campus, Guildford, United Kingdom
246639
Last updated: 10/09/2024






About Master of Science - Computer Vision, Robotics and Machine Learning
The University of Surrey's Computer Vision, Robotics and Machine Learning MSc is best suited for students who are intrigued by artificial intelligence (AI), the application of robotics and creating machines that can ‘see’. This course is taught by academics from University's 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.
On this course, students will gain in-depth training and hands-on learning experiences in deep and machine learning, robotics and automation, and image and video analysis. They'll also explore low-level image processing methods. Moreover, there is an opportunity for learners to substantially expand their programming skills through the projects they choose to take on. During the first semester, students 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 the second semester. From that point, they’ll have approximately two and a half months to complete the work and write up their dissertation.
The University draws on its industry experience to inform and enrich teaching, bringing theoretical subjects to life. Some of the industrial collaborations include research and technology transfer projects with industrial partners such as the BBC, Foundry, LionHead and BAE. Uniquely, the robotics material is inspired by the University of Surrey Space Centre, building on the specialisms in space robotics.
This MSc programme is accredited by the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for Further Learning for registration as a Chartered Engineer. However, candidates must hold a CEng accredited BEng or BSc (Hons) undergraduate first degree to comply with full CEng registration requirements.
The University has 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.
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