COURSE CURRICULUM

The core and optional modules of the MSc Data Science and Applied Analytics program provide a comprehensive foundation in data science theory, practical skills, and research capabilities. Big Data Analytics and Modelling introduces methods for handling, analysing, and interpreting large-scale datasets, while Data Programming in Python equips students with essential coding skills for implementing data-driven solutions. Fundamentals of Data Engineering focuses on designing and managing data architectures, pipelines, and workflows, supporting efficient data processing and analysis. Introduction to Data Mining and Image and Text Processing for Data Science develop expertise in extracting insights from structured and unstructured data, including textual and visual information. Simulation, Mathematical and Statistical Modelling enhances students’ ability to apply quantitative techniques to solve complex problems and model real-world phenomena. Frontiers of Data Science Research exposes students to emerging trends and innovations in the field, fostering critical thinking and awareness of cutting-edge approaches. Research Methods equips students with rigorous methodological skills, preparing them for academic or applied research. The Research Project allows students to undertake an independent investigation, integrating theory, technical skills, and practical applications. The optional Professional Practice module provides exposure to real-world industry contexts, helping students translate their knowledge into professional experience. Together, these modules prepare graduates to analyse complex datasets, develop analytical tools, and provide actionable insights across business, public sector, and research environments.