Machine Learning for Visual Data Analytics MSc

Queen Mary University of London

As recent developments in computers and sensors make the generation, storage and processing of visual data easier, methods that enable a machine to analyse and understand images and videos become increasingly relevant. The advances in this field are behind Google's autonomous vehicles, Meta's image analysis technologies and car plate recognition systems.This programme is designed to train engineers to work in the analysis and interpretation of images and video.Undertake high-level training in programming languages, tools and methods necessary for the design and implementation of practical computer vision systems.Be taught by world-class researchers in the fields of multimedia analysis, vision-based surveillance, structure from motion and human motion analysis.Work on cutting-edge research projects, gaining hands-on experience.What you'll studyThis course will enable students to study cutting-edge technologies in the field of machine learning for visual analytics, and will provide them with the background and skills they need to pursue careers in research or industry. Course content covers:Fundamental methods and techniques in computer vision, machine learning and image processing.Programming tools, languages and techniques for the application of machine learning methods to analyse visual data.Methods and techniques for systems and applications.The programme is taught by academics from the Computer Vision and Multimedia and Vision research groups. The groups consist of a team of more than 100 researchers (academics, post-docs, research fellows and PhD students) performing world-leading research into the fields of surveillance, face and gesture recognition, multimedia indexing and retrieval and robotics.The School has collaborations, partnerships, industrial placement schemes and public engagement programmes with organisations including Vodafone, Google, IBM, BT, NASA, BBC and Microsoft.This degree is accredited by BCS, The Chartered Institute for IT, for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional. This degree is also accredited by BCS on behalf of the Engineering Council, for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer.

School of Electronic Engineering and Computer Science