Course Curriculum

The Data Analytics options require students to complete a total of thirty credit points selected from a range of advanced electives designed to build strong analytical, statistical, and machine learning capabilities. These subjects provide both theoretical depth and practical skills, enabling students to work confidently with complex data and advanced analytical techniques across diverse applications.Core statistical foundations are strengthened through subjects such as Mathematical Statistics, Stochastic Processes, Survival Analysis, and Advanced Econometrics, which develop rigorous quantitative reasoning and support high-level data analysis and modelling. These subjects equip students with the ability to understand uncertainty, analyse time-to-event data, and apply econometric methods to real-world problems.Students can also focus on modern data science and machine learning through electives such as Infrastructure for Data Analytics, Deep Learning Through Neural Networks, Statistical Learning and Regression Models, Modern Machine Learning Models, and Advanced Statistical Learning Models. These subjects explore contemporary analytical tools, algorithms, and computational frameworks used to process large datasets and extract meaningful insights.Together, these electives allow students to tailor their studies to their interests and career goals, whether in statistics, econometrics, or machine learning–driven analytics. By completing these thirty credit points, students develop advanced technical expertise and analytical skills that are highly valued across industries, preparing them for roles in data analytics, data science, research, and other data-driven professional fields.