50業子

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.
• You���ll 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.
• You���ll develop the transferrable skills you need to be successful in any field. For example, by the end of the course, we expect that you���ll 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.