Course summary

Why choose this course Collecting, managing and analysing data is essential across many sectors – from finance to politics, and advertising to healthcare. This data science masters degree will give you the advanced computation and mathematics skills you’ll need to work in the growing field of data science. Designed in collaboration with industry and drawing on leading research, our Data Science MSc will prepare you for a career as a data scientist, data analyst, data engineer, data architect or a business analyst. Our data science masters uniquely addresses the fundamentals of data as well as the technical considerations needed to handle data with increasing scale and complexity. What you will study Our Data Science MSc, designed in collaboration with industry, combines in-depth study of the theory and practice of data science with an optional year-long work placement, where you’ll get the chance to apply your knowledge to industry-relevant challenges. A placement also allows you to discover the business value of data-oriented research and development. During the MSc you will gain experience in working with real-world data sets through the entire data analysis pipeline. You’ll acquire solid technical knowledge of current methods in machine learning and statistics, and their application in a business setting. We also cover important practical topics such as building and querying databases and working in the cloud. Through our optional module choices, you can customise your MSc to specialise in topics such as Natural Language Processing, Deep Learning and advanced methods in AI and machine learning. You’ll also complete a dissertation where you can further explore an area that interests you with guidance from a supervisor. Our dissertation projects involve topical real-world problems, often linked into cutting-edge research. Before starting your dissertation you will learn how to approach a research project, including how to search the academic literature effectively and write up your findings, as well as ethical and security concerns specific to data science.