Masters | Postgraduate Course - Machine Learning for Visual Data Analytics MSc Course Details within Queen Mary University of London

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Course Fees
Home and EU students 2018/19 Academic Year Full time £9,250 Part time £4,650 International students 2018/19 Academic Year<br /> Full time £19,500 Part time £9,750
Start Month(s)
Contact Name
School of Electronic Engineering and Computer Science
+44 (0)20 7882 7333
Machine Learning for Visual Data Analytics MSc

Study Details

MSc 1 year Full time 2 years Part time

How can we design smartphones that sense your mood by reading your facial expressions or recognise hand gestures as a way to make a call? How do we develop systems that quickly and reliably analyse medical scans to assist with cancerous tumour diagnosis or improve the safety of self-driving cars with in-vehicle technology able to detect and modify a vehicle’s behaviour in any environment? These are just some of the fascinating questions that you will strive to answer on this programme.

This programme is intended to respond to a growing skills shortage in research and industry for engineers with a high level of training in the analysis and interpretation of images and video. It covers both low-level image processing and high-level interpretation using state-of-the-art machine learning methodologies.

In addition, it offers high-level training in programming languages, tools and methods that are necessary for the design and implementation of practical computer vision systems. You will be taught by world- class researchers in the fields of multimedia analysis, vision-based surveillance, structure from motion and human motion analysis. Aside from your lectures, you will be working on cutting-edge, live research projects, gaining hands-on experience.

Module details

 Semester 1

  • Machine Learning (15 credits)
  • Introduction to Computer Vision (15 credits)

Plus two options from:

  • Computer Graphics (15 credits)
  • Big Data Processing (15 credits)
  • Data Mining (15 credits)

Semester 2

  • Deep Learning and Computer Vision (15 credits)
  • Machine Learning for Visual Data Analytics (15 credits)

Plus two options from:

  • Digital Media and Social Networks (15 credits)
  • Artificial Intelligence (15 credits)
  • Image Processing (15 credits)

Semester 3
(must take and pass)

  • Project (60 credits)

Entry Requirements

An upper second class degree is normally required, usually in electronic engineering, computer science, maths or a related discipline. Students with a good lower second class degree may be considered on an individual basis. Applicants with unrelated degrees will be considered if there is evidence of equivalent industrial experience.

Programme Funding

There are a number of sources of funding available for Masters students.

These include a significant package of competitive Queen Mary University of London (QMUL) bursaries and scholarships in a range of subject areas, as well as external sources of funding.

Student Destinations

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