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  • DeadlineStudy Details: MSc 1 year full-time, 2 years part-time

Masters Degree Description

This is an interdisciplinary programme that provides a solid foundation in data analytics and artificial intelligence. You’ll be taught principally by the School of Mathematical Sciences, with the option to choose modules from the Business School. Our unique curriculum teaches you how various approaches in data analytics and AI can be applied to decision making in modern, data-rich environments.

In addition to the core data analytics component, the programme includes options to specialise in:

  • Modelling and AI for health sciences and pharmacology
  • Data-driven techniques for business analytics
  • Statistical machine learning and AI

The flexible structure gives you an opportunity to specialise or keep your options open, aligning your education with your career goals and interests.

During the course, you‘ll develop a strong mathematical foundation along with practical and interdisciplinary skills. You‘ll also learn the theory behind data analytics and AI, gaining insight into the "why" behind algorithms and methods, and practise tackling real-world challenges.

Entry Requirements

2:1 BSc degree in mathematics, physics, economics, computer science, natural sciences or engineering. A solid background in mathematics, including calculus, linear algebra and the basics of probability and statistics.

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Fees

For fees and funding options, please visit website to find out more.

Student Destinations

Graduates of this programme are industry-ready and can go on to pursue careers in technology, finance, healthcare and more. With strong maths and computational skills, graduates can understand and use complex data analytics and AI methods, making them highly desirable in the job market.

Graduates from the School of Mathematical Sciences go on to work for top employers such as Capital One, Kubrick Group, BAE Systems, Amazon, BP and China Zheshang Bank.

Module Details

Core modules

  • Applied Statistics and Probability20 credits
  • Project in Data Analytics and AI60 credits

Optional modules (autumn)

  • Foundations of Data Analytics20 credits
  • Foundational Business Analytics20 credits
  • Data at Scale: Management, Processing and Visualisation20 credits
  • Mathematical Medicine and Biology20 credits
  • Application Driven Biomedical Modelling20 credits
  • Advanced Statistical Inference20 credits
  • Statistical Modelling with Machine Learning20 credits
  • Optimization20 credits
  • Financial Mathematics20 credits

Optional modules (spring)

  • Analytics Specialisations and Applications20 credits
  • Machine Learning and Predictive Analytics20 credits
  • Applied Multivariate Statistics20 credits
  • Bayesian Data Analysis20 credits
  • Neural Networks and AI20 credits
  • Data Science for Structured Data20 credits
  • Model-informed Pharmacology20 credits
  • Biomedical Modelling in an AI World20 credits
  • Computational Applied Mathematics

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