There is a quite a bit of Mathematics on the course as would be expected in an MSc focused on Data Science. Students are expected to understand the mathematics underpinning a variety of data science techniques. This permits correct interpretation of results, and informs optimisations of algorithms used. For example, the Algorithms for Data Science module covers the maths behind 10+ algorithms. Some are based on statistics (e.g. Naïve Bayes, Bayesian Networks, Regression), some are based on AI / Machine Learning (Neural Networks, Decision Trees) and some are based on set theory such as Apriori and FPGrowth.  The Statistics module covers statistical techniques in depth.