University of Surrey vs University of Nottingham

Collecting, managing and analysing data is essential across many sectors – from finance to politics, and advertising to healthcare. This course 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.

This programme uniquely addresses the fundamentals of data as well as the technical considerations needed to handle data with increasing scale and complexity.

Big data is playing an increasingly important role in our society. The need for expert and ethically-informed data analysis is in high demand across many industries. This course gives you the professional and problem-solving skills for a range of high-level careers.

This interdisciplinary masters will be taught by the Schools of Computer Science and Mathematical Sciences. The academics conduct their own international-quality research. They use this to teach you the latest techniques and technologies in this field.

Develop your knowledge in key topics such as statistical modelling, machine learning and advanced algorithms. This course offers a range of flexible optional modules. This allows you to study a topic that interests you.

You will undertake an individual research project in an area of your choice. This can be with industry partners or with one of our expert research groups. Past projects have included:

Development of location-based service for education
UK precipitation forecasting
The effect of virtual audiences on music performance anxiet

A minimum of a 2:2 UK honours degree in computer science, electrical or electronic engineering, mathematics, physics, related disciplines with demonstrable exposure to programming and mathematics, or other alternative subjects related to data analysis, data science or informatics, or a recognised equivalent international qualification.

• 2:1 (or international equivalent) with an affinity for programming and/or advanced statistics evidenced through prior study or practical experience detailed in the application. Graduates from other fields, with strong mathematics and/or computer science background will be considered with 60% average mark.

In this fast-paced, data-driven modern world, business analysts help organisations turn big data into big ideas. Artificial intelligence, machine learning and management science power decisions in business. You’ll gain data-led insights and optimise businesses by using descriptive, predictive and prescriptive analytics. 

This highly practical MSc Business Analytics course will transform you into a confident lateral thinker who is up to date on the latest theory and practice. While you benefit from the input of inspiring industry experts, in class and on-site, the university will also make sure you’re immersed in the business problems faced by the global business community today.

Business Analytics MSc is taught in collaboration with multinational companies and will give you the essential skillset they are looking for. It has been developed by the Neo-demographic Laboratory for Analytics in Business (N/LAB), a state-of-the-art teaching, data visualisation and research facility within the Business School.

You will benefit from the engagement of N/LAB's multi-national partners through their support for teaching and access to data.

You have the option to take industry-recognised digital qualifications by Microsoft and SAP alongside your course, which will develop your digital skills.

The course will help you to become a business-orientated data scientist with a technical skillset, the ability to harness big data tools and the managerial skills to deliver practical business analytics projects. It will prepare you for senior management positions within the broad scope of the digital economy.

A minimum of a 2:1 UK honours degree in either computer science, economics, engineering, finance or mathematics, or a recognised equivalent international qualification.

2:1 (or international equivalent) in any discipline; applicants should not have previously studied a significant amount of business analytics, but must have a 2:1 (or international equivalent) in quantitative modules at degree level with a significant amount of mathematical/statistical content