Data Science with a Year in Industry

Data science is the discipline of extracting meaningful knowledge from data: the theory and practice of collecting, cleaning, analysing, modelling and interpreting large and complex datasets to support decisions in business, government, healthcare, science and beyond. It combines statistics, computer science, mathematics and domain knowledge, and it sits at the centre of one of the most significant transformations in how organisations understand themselves and the world around them. As data becomes an increasingly fundamental asset, the ability to work with it rigorously and creatively is among the most valuable professional skills available.

At the University of Kent, this four-year full-time degree includes a year in industry, giving you extended professional experience in a data science or analytics role before you complete your studies. You will cover the statistical and mathematical foundations of data science alongside the computational skills needed to implement methods at scale: probability and inference, machine learning, statistical modelling, data visualisation, programming in relevant languages and the management and processing of large datasets. The programme is designed for students with an affinity for mathematics and statistics who want to apply those skills to the challenge of extracting valuable insights from complex real-world data.

Typical entry is around 104 UCAS tariff points.

Data science graduates are in exceptionally high demand across virtually every sector. Roles include data scientist, data analyst, machine learning engineer, business intelligence analyst, data engineer, quantitative analyst and research scientist in organisations ranging from technology companies and banks to healthcare providers, public sector bodies, retail businesses and scientific institutions. The year in industry significantly strengthens graduate employability by providing professional credits and industry connections before graduation.

Further study in data science, machine learning, statistics or a domain specialisation is available for those who wish to develop deeper expertise.