Data Science - MSc

Program Overview

Kent's MSc Data Science conversion course tailors to those with non-related backgrounds, providing foundational knowledge and practical skills required in the field. Led by research-active experts, students learn cutting-edge machine learning and deep learning methods, as well as transferrable skills, preparing them for roles in various industries where data analysis is crucial.

Program Outline

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. This conversion course is designed for those with limited previous knowledge of data science, statistics and computing: 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.

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

Assessment:

Assessments include extensive analyses of complex real-world data. There will be unseen written examinations but most of the credit is based on coursework, including an independent project and report supported by an academic supervisor. Assessments will involve working with messy data where analyses need to be presented to 'clients', group work on coding projects, and development of data visualisation tools that could be used by a particular organisation. There will be exposure to assessments that are relatively low stakes, such as project plans and presentations. The technology to be used to undertake assessment will be standard: any computer with a modern specification will be appropriate.

Teaching:

Our expert teaching staff are leaders in their field who use innovative teaching methods to bring the subject to life. Programme aims and learning outcomes are set to ensure you get the most from your study.

Careers:

You will be a trained data scientist, equipped to work in many fields.

Other:

Kent is a leading research university, meaning that you will be informed about new discussions and developments by the people making them. This means your work will have real potential to make a difference.

Research Themes:

• Statistical Ecology
• Bayesian statistics
• Biological and health statistics
• Machine learning
• Nonparametric statistics
• Economics and finance

The 2024/25 annual tuition fees for this course are: Data Science - MSc at Canterbury Data Science - PDip at Canterbury Data Science - PCert at Canterbury For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated. Your fee status The University will assess your fee status as part of the application process. For students continuing on this programme, fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.

Your fee status The University will assess your fee status as part of the application process. Additional costs General additional costs Funding You may find it helpful to look at both: University and external fundsScholarships specific to the academic school delivering this programme.