Queen Mary University of London

Queen Mary University of London

Big Data Science

We offer Industrial Experience options on all our full-time taught MSc programmes, which combine academic study with a one-year industrial placement between your taught modules and summer project. Taking the Industrial Experience option as part of your degree gives you a route to develop real-world, practical problem-solving skills gained through your programme of study in a professional context. This programme is designed for those who want to pursue a career as data scientists, deriving valuable insights and business relevant information from large amounts of data. You will cover the fundamental statistical (e.g. machine learning) and technological tools (e.g. cloud platforms, Hadoop) for large-scale data analysis. The big data science movement is transforming how Internet companies and researchers over the world address traditional problems. Big data refers to the ability of exploiting the massive amounts of unstructured data that is generated continuously by companies, users, devices, and extract key understanding from it.

Entry requirements

You should have a 2nd-Class degree or above (good 2.1 minimum for Industrial Experience option) in electronic engineering, computer science, mathematics, or a related discipline. Applicants with unrelated degrees will be considered if there is evidence of equivalent industrial experience. For international students whose 1st language is not English, we require English language qualifications IELTS 6.5 or TOEFL 92 (internet based) or equivalent qualification.

Course modules

The MSc modules cover the following aspects: Statistical Data Modelling, data visualization and prediction; machine Learning techniques for cluster detection, and automated classification; big data processing techniques for processing massive amounts of data; domain-specific techniques for applying data science to different domains: Computer vision, social network analysis, bio engineering, intelligent sensing and internet of things; use case-based projects that show the practical application of the skills in real industrial and research scenarios. Students will be offered lectures that explain the core concepts, techniques and tools required for large-scale data analysis. Laboratory sessions and tutorials will put these elements to practice through the execution of use cases extracted from real domains. Students will also undertake a large project where they will demonstrate the application of Data Science skills in a complex scenario.


Qualification Study mode Start month Fee Course duration
MSc Full-time - 1 years

Campus details

Campus name Town Postcode Region Main campus Campus Partner

Key information

School of Electronic Engineering and Computer Science
Telephone number: 
020 7882 7333