Master of Science - Data Science (Professional Placement)

Data Science is one of the most rapidly expanding areas of employment globally, due to rapid and ongoing developments in computer systems and data gathering. Large data sets are widespread in business, science and government.

This course builds on the established strengths of the Mathematics and Computer Science programmes at Kingston and develops a multidisciplinary approach to the computational analysis of data. There is an increasing demand for data-savvy professionals, both in industry and in research, who are able to make sense of complex datasets, build models and apply them to the solution of relevant problems. Students will get the opportunity to develop their skills in a way which will prepare them for careers in this fast-growing and exciting area.

The multidisciplinary nature of data science is reflected in this MSc programme through the careful combination of modules in data management, analysis, modelling, visualisation and artificial intelligence (AI), which are taught by a cross-disciplinary team whose expertise encompasses mathematics, statistics, AI and machine learning, information management, and user experience design.

Kingston University allow students to take the option of a 12-month work placement as part of their course. The responsibility for finding the work placement is with the student; the university cannot guarantee the placement, just the opportunity to undertake it. They may find securing a professional placement difficult as they are highly competitive and challenging, but they are also incredibly rewarding. It is very important for students to prepare and apply themselves if this is the route they wish to take. Employers look for great written and oral communication skills and an excellent CV/portfolio. As the work placement is an assessed part of the course, it is covered by a student's Student Route visa.

This course offers an excellent foundation aimed at careers contained within the more generic data science umbrella, including data engineer, data analyst and machine learning engineer.