This master’s aims to respond to the 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. This course is designed to equip you with the skills and expertise in the emerging big data mining techniques required for the analysis, interpretation and visualisation of complex, high-volume, high-dimensional, structured and unstructured data from a variety of sources. The learning outcomes of modules, assignments and projects will be clearly stated. The assessment will be marked on how well you achieve these learning outcomes with feedback that will refer to each outcome, as well as providing an overall percentage grade. Students are required to achieve above 40% to pass; anything above 70% is classified as ‘outstanding’. The assessment for the modules vary and include a diverse set of approaches, such as portfolios, essays, papers, phase-tests, posters, presentations and formal exams. On successful completion, you should have knowledge of: the fundamental principles and techniques of data science and computational intelligence; analysing complex, high-volume, high-dimensional, structured/unstructured data from varying sources; the combination of theory and practical application of data science and computational intelligence methods and techniques; and professional, legal, social, cultural and ethical issues related to data science, computational intelligence and an awareness of societal and environmental impact.