Data Science (with Specialisation in Visualization) MSc

Our Data Science (with Specialisation in Visualization) MSc gives you the knowledge, experience and expertise to solve real-world problems and realise data-driven insights for organisations.<br/><br/>Recognition of professional qualifications outside of the UK<br/>From 1 January 2021 there is an update to the way professional qualifications are recognised by countries outside of the UK. <br/>Read our detailed explanation.<br/><br/>About this course<br/>Data Visualisation is an increasingly important part of data science and aims to bridge the gap between the human and data, by supporting human perception and cognition to make sense of data analytics outputs.<br/><br/>The Data Science (with Specialisation in Visualisation) MSc was created in collaboration with a number of high profile industry leaders to address the skills shortage in data analytics. The course brings together students and industry practitioners in a setting which new technologies are developed and translated into industry practice.<br/><br/>This MSc forms part of the following suite of data science courses:<br/>Data Science MSc, PGDip, PGCert<br/>Data Science (with specialisation in Artificial Intelligence)<br/>Data Science (with Specialisation in Statistics) MSc, PGDip, PGCert<br/><br/>What youll learn<br/>Through this course youll receive a comprehensive grounding in theory and application of data science. Youll also gain the ability to apply these skills to real problems in a given application area.<br/><br/>Through project work, youll experience the full lifecycle from design of interactive visualization to experimental evaluation of an advanced visualization approach.<br/><br/>Topics covered in the course include:<br/>cloud computing<br/>Bayesian statistics<br/>machine learning<br/><br/>Your development<br/>We have substantial expertise in data science, focusing on a wide range of application areas. This includes:<br/>healthcare<br/>transport<br/>cybersecurity<br/>smart cities<br/>manufacturing<br/><br/>We are home to the UK’s National Innovation Centre for Data (NICD). We are also a partner of the Alan Turing Institute, the national institute for data science and artificial intelligence. All our academic staff involved in teaching data science modules have international reputations for their contributions to the field. Many of them have extensive experience as practitioners in industry as well as work in academia. You will be encouraged to play a full part in the life of the School of Computing, including:<br/>taking advantage of dedicated computing and study facilities<br/>participating in seminars delivered by researchers and distinguished external speakers<br/><br/>Delivery<br/>The School of Computing and School of Mathematics, Statistics and Physics deliver the course. The course starts in mid-September. You will be taught in modern facilities in the newly-opened Urban Sciences Building. The course has three phases.<br/><br/>In phase one you’ll be introduced to core knowledge and skills in statistics and computer science. These modules are taught as an intensive block, with two modules taught concurrently for full-time students. Teaching is timetabled to accommodate participants from industry, working alongside full-time employment.<br/><br/>Phase two will present further advanced technical modules. You will be introduced to the aspects that underlie all areas of data science practice including:<br/>professionalism<br/>legislation<br/>ethics<br/><br/>This phase also includes a group project in collaboration with industry. Youll develop and evaluate a data science solution to a complex, real-world problem.<br/><br/>Phase three is an individual research and development project. Youll receive personal supervision in one of the School’s research labs in collaboration with industry or with your current employer.<br/><br/>Youll be assessed by a portfolio of practical work, accompanied by an oral interview. There will be no written examinations as part of the Data Science MSc.<br/><br/>If you’re a part time student, you have the flexibility to study over two years. The part time version of the course encourages participation of practitioners from industry.