Data Science explores the areas of statistics, data analysis, and data mining to identify phenomena within data. The module begins by teaching students core skills in statistics and probability, building on ideas initially introduced in Mathematics for Computer Science and the Algorithms module. Statistics and probability are then explored within the concept of computational modelling and simulation, applying stochastic tools so students can simulate data that matches real-world observations.

The second half of the module applies the principles from the first half of the module to undertake data science tasks. Students walk through the process of undertaking data analysis. First, data sourcing, cleaning, and initial processing is undertaken, building on ideas presented in the Databases module. Students then apply tools to transform and analyse the data, allowing them to make decisions based on their observations. This is undertaken mainly in a business context, although other examples will be utilised as appropriate. Students then examine correct ethical practice as a data science, before finalising the module in an exploration of data mining and results presentation.

Data Science continues the work of the Data theme in Computer Science, building on ideas initially introduced in the Databases module, and combining these ideas with concepts from the Mathematics for Computer Science and Algorithms modules. The aim is to ensure students have fluency in data analysis so they can undertake tasks involving data later in the programme. Specifically, data analysis plays an important role in Data Visualisation, Machine Learning, and Data Engineering, and will likely play an important role in most students� Final-Year Project.

*Course content subject to change