Course Curriculum

The Graduate Certificate in Data Science is designed to equip students with essential knowledge and practical skills needed to work effectively with data in modern industry settings. Across two semesters, the course provides a structured progression from foundational concepts to more advanced analytical techniques. In the first semester, students study Introduction to Data Science with Python, a unit that builds core programming abilities and introduces key data handling processes that underpin the entire data science discipline. This is followed by Machine Learning with Scikit-Learn, which requires completion of the introductory Python unit and extends students’ abilities into supervised and unsupervised learning, model evaluation and the application of machine learning tools to real datasets. During the second semester, students undertake Modern Database Management, where they gain practical skills in database design, implementation and optimisation, ensuring they understand how large datasets are stored, retrieved and processed within organisational environments. The final unit, Deep Learning and Emerging Topics in Artificial Intelligence, builds on the machine learning content and introduces students to neural networks, deep learning architectures and contemporary developments in artificial intelligence, giving them insight into advanced technologies shaping the future of data-driven industries. Across these four units, students engage in hands-on work, learn widely used technologies and develop the analytical mindset needed to extract meaningful insights from data. The course is also aligned with industry standards and incorporates real-world applications to ensure students graduate ready to enter data science roles or continue their studies at the master’s level. Overall, this program provides a solid foundation for anyone aiming to build a career in the rapidly expanding field of data science by developing both technical competence and practical problem-solving abilities.