Queen Mary University of London

Course Introduction

We offer Industrial Experience options on all our full'time taught MSc programmes, which combine academic study with a 1'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. The programme is offered by academics from the Networks, Centre for Intelligent Sensing, Risk and Information Management, Computer Vision and Cognitive Science research groups from the School of Electronic Engineering and Computer Science. This is a team of more than 100 researchers (academics, post'docs, research fellows and PhD students), performing world leading research in the fields of Intelligent Sensing, Network Analytics, Big Data Processing platforms, Machine Learning for Multimedia Pattern Recognition, Social Network Analysis, and Multimedia Indexing.

Duration & Attendance Qualification Tuition fees Fee type
1 year
Full Time

Qualifications required:

  • You should have a good 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; e.g. IELTS 6.5 or TOEFL 92 (internet based) or equivalent qualification.