Loading...
Preparing your educational journey
Computer Vision with Industrial Experience logo
Queen Mary University of London logo

Computer Vision with Industrial Experience

Queen Mary University of London
Information last verified July 2026
Tuition GBP 17,450 (Tuition (Full programme)) — International students; GBP 8,700 (Tuition (Full programme)) — EU/EEA students
Degree MSc
Duration 24 months
Deadline Jul, 2026
Delivery On-campus
Location London, United Kingdom
Language English

Program Overview

The Computer Vision with Industrial Experience at Queen Mary University of London is a MSc programme in Computer Science & IT over 24 months, delivered On-campus. This programme equips graduates with advanced knowledge and practical skills for professional and academic careers in the field.

Students gain a rigorous grounding in both the theoretical foundations and applied dimensions of computer science & it. The programme combines coursework, research components, and practical projects that develop critical thinking, problem-solving, and specialist expertise relevant to industry and research needs.

Graduates of the Computer Vision with Industrial Experience programme are well-prepared for careers in academia, industry, government, and the private sector across France and internationally. The programme provides an internationally recognised qualification within the Bologna higher education framework.

Key Program Features

  1. Duration: 24 months
  2. Language of instruction: English
  3. Study mode: On-campus
  4. English requirement: IELTS 6.5
  5. Tuition: GBP 17,450 (Tuition (Full programme)) — International students; GBP 8,700 (Tuition (Full programme)) — EU/EEA students
  6. Location: London, France

Career Opportunities

Graduates of the Computer Vision with Industrial Experience programme are prepared for diverse careers in computer science & it:

  1. Software Engineer / Developer
  2. Data Scientist
  3. Machine Learning Engineer
  4. IT Project Manager
  5. Cybersecurity Analyst
  6. Cloud Solutions Architect

Program Curriculum

Course Structure

  1. Advanced Transform Methods
  2. Emerging Topics in Learning and Vision
  3. Introduction to Computer Vision
  4. Machine Learning
  5. Techniques for Computer Vision
  6. MSc Project
  7. MSc Industrial Placement Project
  8. Artificial Intelligence
  9. Big Data Processing
  10. C++ for Image Processing
  11. Computer Graphics
  12. Real-Time and Critical Systems
  13. Real-Time DSP

Admission Requirements

Academic Requirements

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.

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

English Proficiency: IELTS 6.5 or equivalent.

Tuition & Financial Information

Tuition Fee

GBP 17,450 (Tuition (Full programme)) — International students; GBP 8,700 (Tuition (Full programme)) — EU/EEA students

Tuition fees: GBP 17,450 (Tuition (Full programme)) — International students; GBP 8,700 (Tuition (Full programme)) — EU/EEA students

IELTS requirement: 6.5

Financial Aid & Scholarships

Contact Queen Mary University of London directly for scholarship, grant, and financial aid information for this programme. Many European universities offer merit-based and need-based funding for international and domestic students.

About Queen Mary University of London

Queen Mary University of London logo

Queen Mary University of London

London, United Kingdom

Visit the university profile page to learn more about this institution.

University Profile
  • Application Deadline Jul, 2026
  • Start Date Sep, 2026
  • Language English
  • Duration 24 months