COURSE CURRICULUM

The Artificial Intelligence MSc program offers an in-depth and structured study of key areas in AI, combining theoretical foundations with practical application. The course begins with Neural Systems and Natural Language Processing, covering neural network paradigms and their engineering and cognitive modelling applications. Students explore deep learning techniques for natural language tasks using Python and tools like PyTorch, moving from basic word embeddings to advanced sequence modelling. The second module focuses on Artificial Intelligence for Mobile Robots, introducing students to robot architecture, sensor systems, and control. It includes navigation, mapping, localisation, and the use of algorithms for autonomous operation. The third module, Fuzzy Logic and Evolutionary Computing, presents methods for reasoning under uncertainty and solving complex optimisation problems. Students study fuzzy systems and evolutionary algorithms such as genetic algorithms and swarm intelligence, applying them in practical scenarios. The fourth module, Research Methods and Applied AI, provides students with essential research skills. It explores qualitative and quantitative methodologies, project design, data analysis, ethics, and literature reviews, preparing students for independent research. In the final stage, students undertake a Thesis Project where they independently identify a research problem, develop a proposal, and carry out a substantial investigation under academic supervision. This project integrates the knowledge and skills developed across earlier modules and is aimed at solving real-world challenges using AI. Throughout the course, students are encouraged to reflect critically, engage with contemporary AI tools and practices, and develop both individual and collaborative working skills. Emphasis is placed on applying AI in practical contexts such as robotics, natural language processing, and optimisation. The course is suited for those aiming to pursue careers in AI development, research, or applied technology roles in various sectors, including robotics, data science, engineering, and business analytics, ensuring graduates are equipped for both academic and industry-based opportunities.