Course Curriculum

The Data Science program is designed to equip students with advanced analytical, computational, and practical skills necessary for solving complex real-world problems using data. In the first year, students complete 84 credit points of core courses, which include Practical Data Science with Python, Programming Fundamentals, Database Concepts, Applied Analytics, Data Wrangling, The Data Science Professional, and Advanced Programming for Data Science. These courses establish a strong foundation in programming, statistical analysis, and data manipulation, while fostering the professional skills required for data-driven decision-making. In addition, students select 12 credit points from options such as Big Data Processing, Data Visualisation and Communication, or Case Studies in Data Science, enabling early exposure to applied data science contexts. In the second year, students continue to develop technical expertise by completing 12 credit points in computational or machine learning-focused courses, including Computational Machine Learning, Data Mining, or Machine Learning. An additional 24 credit points are taken from courses not previously completed, reinforcing knowledge in areas like big data, visualization, or case-based applications. Program and research options allow students to specialise or pursue a research-focused path. The Program Option includes completing 24 credit points in a Data Science Postgraduate Project and 36 credit points from elective courses covering algorithms, applied Bayesian statistics, artificial intelligence, deep learning, database systems, social media analytics, optimisation techniques, and more, providing breadth and depth across the field. Alternatively, the Research Option allows students to engage in up to 60 credit points of research-oriented study, including computing research preparation, algorithms, and a Minor Thesis or Project. This structure ensures that graduates gain both practical and theoretical expertise, preparing them for advanced roles in data science, machine learning, analytics, and research-driven positions in industry or academia, while providing flexibility to tailor the program to individual career aspirations.