Data Science and Computational Intelligence MSc

There is a demand for data scientists with the skills to develop innovative computational intelligence applications, capable of analysing large amounts of complex data to inform businesses decisions and market strategies. Study topics in big data management, data protection and data ethics, statistical modelling, machine learning, deep learning, computer vision, natural language processing, generative AI and reinforcement learning.Explore how data science can be used to extract meaningful insights from both structured and unstructured data, leveraging concepts and tools from mathematics, statistics, computer science, machine learning and related disciplines.Learn about computational intelligence and how it plays a pivotal role in solving complex problems and simulating human-like intelligence in computational systems. Why you should study this course Comprehensive technical knowledge - get an in-depth understanding of a broad range of concepts, algorithms, models, applications, and issues in data science and computational intelligence.Advanced AI applications - engage deeply with complex challenges in natural language processing, reinforcement learning, computer vision, big data management and statistical modelling.Ethics and responsibility - learn about critical legal, ethical, social and professional aspects, including responsible AI use, bias mitigation, data protection, transparency and sustainability.Research-informed teaching - study a course that has been designed in collaboration with Coventry University’s Centre for Computational Science and Mathematical Modelling. Our current research staff are involved in teaching some modules, supervising student projects and using current research to inform curriculum content.Professional placement opportunity - gain practical experience and boost your CV with an additional professional placement. See the modules for more details.

An honours degree 2:2 or above (or international equivalent) in a relevant discipline such as computer science, mathematics, statistics or engineering.