COURSE CURRICULUM

The BSc (Hons) Artificial Intelligence and Data Science curriculum develops strong foundations in mathematics, computing, artificial intelligence, and data science through a progressive three-year programme. In the first year, students study core modules including Logic and Discrete Mathematics, Introduction to Probability and Statistics, Calculus, Programming, Introduction to Data Science and Modelling, and Professional Work Skills. These modules establish essential knowledge in algebra, logic, discrete mathematics, probability, statistics, calculus, programming, and data modelling while developing problem-solving, computational thinking, and professional skills. Students learn key mathematical concepts such as sets, functions, Boolean logic, matrices, graphs, networks, trigonometry, vectors, and complex numbers, providing the foundation for advanced AI and data science studies. In the second year, students strengthen their technical expertise through core modules in Legal, Ethical and Sustainability Issues, Team Project, Linear Algebra, Statistical Methods for Data Analysis, and Introduction to Machine Learning, with optional modules in Operational Research and Functional Programming. These modules develop knowledge of machine learning algorithms, statistical analysis, linear algebra, collaborative software development, and the legal, ethical, privacy, security, intellectual property, and sustainability issues associated with modern computing technologies. Students also gain practical experience through team-based projects that simulate real-world software and data science environments. In the final year, students advance their knowledge through core modules including Statistical Modelling, Frontiers in Artificial Intelligence and Data Science, Deep Learning, and an Individual Project, with optional modules such as Advanced Analytics and Optimisation Techniques. Students explore advanced statistical methods including linear regression, generalised linear models, Bayesian techniques, deep learning, and the latest developments in artificial intelligence and data science while applying industry-standard tools and computational techniques to solve complex real-world problems. The Individual Project enables students to undertake independent research and develop innovative AI or data science solutions to practical challenges. Overall, the curriculum combines rigorous mathematical foundations, programming, statistical analysis, machine learning, artificial intelligence, and practical project work to prepare graduates for careers in artificial intelligence, data science, machine learning engineering, business analytics, software development, research, and digital innovation across a wide range of industries.