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Study at the University of Kent

 Canterbury, United Kingdom

Data Science
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Data Science

Master of Science at the University of Kent

Programme details
Degree: Master of Science (MSc)
Disciplines: Data Science & Big Data
Statistics
Duration: 1 year
Study modes: full-time, part-time
University website: Data Science

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Description:

Overview

Data scientists use principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering, to analyse and generate meaning from data. At Kent, you're taught how to apply cutting-edge machine learning and deep learning methods, and how to make sense of the text data that is all around us.

Taught by experts in the field, you'll use real-world data to learn the technical, practical and transferrable skills needed to be a successful data scientist. You don't need a background in the subject as we start with the foundations of data science theory.

Artificial intelligence and machine learning innovations have made data processing faster and more efficient. Industry demand has created job positions in organisations around the world within the field of data science. Due to the skillset and expertise required, this looks likely to continue over the coming decades. Add an Industrial Placement to further enhance your employability.

Reasons to study MSc Data Science at Kent

  • Our course is tailor-made to allow entry with an undergraduate degree from any subject (or equivalent qualifications or experience), so long as you meet our entry requirements.
  • The course was designed in consultation with external organisations; they told us which skills and experience they look for in potential employees.
  • Youll be taught key technical skills that employers expect from their employees, including Python and R programming and the use of machine learning and deep learning methods.
  • Youll develop the transferrable skills you need to be successful in any field. For example, by the end of the course, we expect that youll be much more confident in presenting your findings in various ways to other people.
  • You can add an industrial placement to your degree course, allowing you to gain valuable work experience and contacts.
  • Our teaching staff are research-active and have a wide range of experience. Our expertise covers the broad subject of data science.

About the School of Mathematics, Statistics and Actuarial Science (SMSAS)

The School has a strong reputation for world-class research and a well-established system of support and training with a high level of flexibility, and frequent contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School, setting you up for a great career.

About the School of Computing

Our world-leading researchers, in key areas such as cyber security, programming languages, computational intelligence and data science, earned us an outstanding result in the recent Research Excellence Framework (REF) 2021; an impressive 100% of our research was classified as either 'world-leading' or 'internationally excellent' for impact.

Strong links with industry underpin all our work, notably with Cisco Systems Inc, Microsoft, Oracle, IBM, Nvidia, Erlang Solutions, GCHQ and Google.

Our programmes are taught by leading researchers who are experts in their fields. The School of Computing at Kent is home to several authors of leading computer science textbooks.

We have a large range of equipment providing both Linux and PC-based systems. Our resources include a multicore enterprise server and a virtual machine server that supports computer security experiments. 

The School has superb makerspaces including Hackspace, which houses cutting-edge technology and equipment, and the Cognitive Robotics and Autonomous Systems LabAmong other equipment it contains a milling machine, 3D printers, laser cutter and extensive space for building and making digital artefacts.

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Find more information on the website of the University of Kent:

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