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Machine Learning for Visual Data Analytics MSc

Machine Learning for Visual Data Analytics MSc

Different course options

Full time | Mile End | 1 year | 16-SEP-24

Study mode

Full time

Duration

1 year

Start date

16-SEP-24

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Data Analysis Artificial Intelligence (Ai)

Course type

Taught

Course Summary

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, Facebook'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.

This 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.

Career paths

Your skills and knowledge will be valuable in all industries that require intelligent processing and interpretation of image and video. This includes multimedia indexing and retrieval (eg Google, Microsoft), motion capture (eg Vicon), media production (eg Sony, Technicolor, Disney), medical imaging, security, defence (eg Qinetiq) and robotics, as well as other industries that require good knowledge of machine learning, signal processing and programming.

A number of our academics have common research projects with industrial partners such as Disney, BBC, Technicolor and STMicroelectronics, and take on consultancy work within the industry.

You will also be ideally placed to pursue further research and PhD studies.

Modules

In recent years, research in computer vision has made significant progress. This is largely driven by the recognition that effective visual perception is crucial in understanding intelligent behaviour - unless we understand how we perceive, we will never understand how we reason The first part of the module will introduce the relevant concepts and techniques in machine learning. In the second part we will show how these techniques can be applied to various areas in computer vision.

Tuition fees

UK fees
Course fees for UK students

For this course (per year)

£12,650

International fees
Course fees for EU and international students

For this course (per year)

£28,900

Entry requirements

Students need to have a 2:1 or above at undergraduate level in Electronic Engineering, Computer Science, Mathematics or a related discipline.

University information

Queen Mary University of London (QMUL) is an internationally regarded public research institution based in London. It has a long history, dating back over 230 years, and is a member of the prestigious Russell Group of universities. Queen Mary has five campuses in the city of London and an international network of satellite campuses in China, Malta, Paris and Singapore. There is a population of around 16,000 students at the London campuses and...more