COURSE CURRICULUM

This data science course offers a rich and multidisciplinary curriculum that combines advanced statistical, computational, and analytical techniques to prepare students for diverse roles in the field. It begins with modules such as Statistical Inference for Data Science and Fundamentals of Statistical Modelling, which establish a solid foundation in probability, estimation, and data analysis. Scientific Computation introduces numerical methods and programming skills essential for processing large and complex data. Students also gain hands-on experience with data storage and management through the Database Systems in Practice module. The course delves into Text Analytics and Natural Language Processing, allowing students to explore techniques for extracting insights from unstructured textual data.Further, the Statistical Learning module introduces algorithms for supervised and unsupervised learning, enhancing students' ability to identify patterns and make predictions. Quantitative Research Methods for Science, Engineering and Technology equips students with essential research skills applicable across technical domains. Networks and Complex Systems examines the structure and behavior of interconnected systems, which is vital in areas such as social media, biology, and communication networks. The Applied Big Data and Visualisation module focuses on large-scale data processing and the use of visual tools to interpret data effectively. Artificial Intelligence and Machine Learning extends the analytical capabilities of students by exploring intelligent systems and learning algorithms that mimic human decision-making.A key feature of the course is the research project and dissertation, through which students apply their learning to a focused area of interest. They have the option to specialise in one of three sub-disciplines: Mathematics and Statistics, Electronic and Computer Engineering, or Computer Science and Information Systems. This allows for a tailored educational experience that aligns with each student’s background and career goals. Overall, the course provides a comprehensive blend of theory and practice, preparing students for success in the rapidly evolving data science industry.