COURSE CURRICULUM

The Statistics with Data Analytics MSc at Brunel University provides a comprehensive program designed to equip students with advanced theoretical knowledge and practical skills in statistical analysis and data science. Core modules focus on computationally intensive statistical methods, enabling students to interpret results accurately, create regression algorithms, and manage massive datasets. Students develop expertise in data mining and artificial intelligence, applying machine learning techniques such as clustering, regression, support vector machines, decision trees, and neural networks to extract value from complex, heterogeneous data. Financial markets, probability, and stochastic methods are introduced to provide a foundation for quantitative modelling and risk assessment, while machine learning and quantitative data analysis modules equip students with skills in regression, classification, multivariate methods, and data visualisation. Research methods and case study modules further develop critical thinking, problem-solving, and industry-relevant skills to prepare students for applied research and practical projects. Time series forecasting and risk modelling teach students to apply predictive models to financial and operational decision-making. The program culminates in a dissertation, allowing students to undertake independent research, synthesising theoretical concepts with practical data analysis to explore advanced topics in statistics and data analytics. This combination ensures graduates are highly competent and employable in data-driven industries, research, or further study.