Companies need people who can take data and transform it into a powerful strategic asset. This specialisation provides a rigorous, practical foundation in the key skills needed to unlock the value of data, and an in-depth understanding of how companies can use data to make decisions and improve business performance.
Business Analytics (with specialisation in Management Science) is taught by UCL School of Management (in conjunction with UCL Computer Science). It combines modules that explore how data and analytics are transforming key areas of business (decision-making, strategy, marketing, operations) with modules that provide the mathematical and computational skills needed to make effective use of the latest business analytics tools.
Students undertake modules to the value of 180 credits. The programme consists of six core modules (90 credits), two optional modules (30 credits) and a dissertation/report (60 credits).
Core modules -Business Strategy and Analytics -Marketing Analytics -Mathematical Foundations for Business Analytics -Programming for Business Analytics -Predictive Analytics -Operations Analytics
Optional modules - students take two optional modules from a selection of elective modules offered by the UCL School of Management and the UCL Department of Computer Science. Possible electives, subject to agreement, will cover topics including software engineering, practical machine learning, project management and social network analytics.
Dissertation/report All students undertake an independent research project which culminates in a dissertation of 15,000 words.
Teaching and learning The programme is delivered through a combination of lectures, seminars, tutorials and project work. Assessment is through unseen written examinations, coursework and the dissertation.
The world is changing: more than 30 billion pieces of content are shared on Facebook every month; and companies are capturing trillions of bytes of information about their customers, suppliers, and operations. This explosion of data is disrupting industries and creating new opportunities.
Companies need people who can take data, understand it, process it, extract value from it, visualise it, and communicate it.
They need people who deeply understand data, its potential and its limitations, who can frame business problems, analyse data with statistical techniques, develop and maintain predictive models, and communicate analytics results to business executives, partners and customers.
Employability Graduates from this new programme will be highly employable in global companies and high-growth businesses, finance and banking organisations, and consulting firms.
Students will develop strong quantitative and analytical skills, an in-depth understanding of how companies use data to make decisions and improve business performance, and practical experience with leading business analytics tools. They will be equipped to influence strategy and decision-making, and be able to drive business performance by transforming data into a powerful and predictive strategic asset.
Why study this degree at UCL?
Business Analytics requires a combination of management insight, strong quantitative and analytical skills, and an understanding of the technology required to handle data at scale.
UCL School of Management offers innovative undergraduate, postgraduate, and doctoral programmes to prepare people for leadership roles in the next-generation of innovation-intensive organisations. The department works closely with global companies and high-growth businesses at the cutting-edge of management practice. UCL Computer Science is a global leader in research in experimental computer science.
Students on the Business Analytics (with specialisation in Management Science) MSc will benefit from the extensive industry networks of both departments.
A minimum of an upper second-class UK Bachelor’s degree or an overseas qualification of an equivalent standard. Applicants must have a strong aptitude for quantitative analysis and are likely to have studied a range of degrees including: management, mathematics, engineering, computer science, economics, and psychology.
Recipient: University College London
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