Machine Learning for Visual Data Analytics MSc

1 Year On Campus Masters Program

Queen Mary University of London

Program Overview

This MSc trains students in advanced machine learning, deep learning, image processing and computer vision for interpreting images and video. It suits students with computing, mathematics, or engineering backgrounds who want to specialise in visual data analytics, robotics vision, medical imaging, or AI-based visual systems.

Curriculum Structure

Year of Study (Full-time)

Students begin with core modules such as Machine Learning, Introduction to Computer Vision, Applied Statistics, and either Natural Language Processing or Computer Graphics, building foundations in algorithms, statistical modelling, and visual data fundamentals.
They then advance to modules like Deep Learning and Computer Vision, Machine Learning for Visual Data Analysis, and Image Processing, learning to design neural networks, extract features, classify images, and analyse complex visual datasets.
The year concludes with an Independent Project, where students develop a full visual-analytics or computer-vision system, applying deep learning and image-processing methods to a real dataset or research problem.

Focus areas: “Machine learning; deep learning; computer vision; image processing; visual data analytics; neural-network modelling; applied vision projects”

Learning outcomes: “Build and train ML and deep-learning models; analyse and process images and video; design computer-vision pipelines; evaluate visual-data systems; complete an advanced applied or research project”

Professional alignment: Designed to meet industry expectations for careers in visual AI, computer vision engineering, multimedia analytics, robotics vision, and imaging-based applications.

Reputation: Taught within a strong UK research environment in AI and computer vision, enhancing graduate employability in high-demand sectors such as autonomous systems, healthcare imaging, surveillance, robotics, and media technology.

Experiential Learning (Research, Projects, Internships etc.)

The MSc Machine Learning for Visual Data Analytics at Queen Mary University of London provides intensive practical programming and analytical skills for students from non-computing backgrounds. Students apply core AI and data science techniques using professional tools in dedicated computing facilities.

Key experiential components:

Software & Tools: Foundational to advanced programming in Python (Pandas, NumPy, scikit-learn, TensorFlow/PyTorch), data management with SQL, and analysis within Jupyter notebooks, using Git for version control.
Computing Facilities: Access to Queen Mary's High-Performance Computing (HPC) facilities and teaching labs within the School of Electronic Engineering and Computer Science, equipped for data-intensive computing and machine learning.
Group Projects: A significant collaborative software and analytics project, where student teams work together to design, build, and evaluate a data-driven AI application, simulating a professional development environment.
Applied Conversion Focus: The programme is designed to build a strong technical portfolio from the ground up. The final individual project is a substantial piece of work, applying data science and AI methods to a substantial problem, often with a research or industry application.

Progression & Future Opportunities

Graduates of Queen Mary University of London's MSc Machine Learning for Visual Data Analytics secure roles as computer vision engineers, machine learning specialists, data analysts, and visual AI developers in multimedia indexing, medical imaging, security, surveillance, robotics, and autonomous systems at companies like Google, Microsoft, Sony, Disney, and Qinetiq:

Careers Service provides CV workshops, interview coaching, industry networking events, and alumni support for research-to-industry transitions.
High demand yields excellent employability; competitive salaries reflecting specialist skills in vision AI (£35k+ UK start).
Collaborations with Google, Microsoft, NASA, BBC via research projects in computer vision and multimedia analysis.
Advanced ML/vision skills support certifications for senior technical leadership.
Strong outcomes in media production, healthcare imaging, security systems, or R&D.

Further Academic Progression: Graduates can pursue PhD in computer vision, machine learning, or AI at QMUL/other institutions, extending research projects on image analysis or neural networks into advanced doctoral work.