COURSE CURRICULUM

This Artificial Intelligence programme provides students with advanced theoretical knowledge and practical skills required to design, develop, and evaluate intelligent systems for real-world applications across multiple industries. The course begins with Artificial Intelligence Foundations, where students gain an understanding of core AI concepts including logic-based knowledge representation, reasoning techniques, problem solving, algorithms, planning, and the development of intelligent applications. Students further develop their expertise through Machine Learning, studying predictive modelling, statistical analysis, probability theory, learning algorithms, and inference techniques that enable computers to learn from data and make decisions without explicit programming. The programme also includes Statistical Methods for Data Analytics, which equips students with practical knowledge of quantitative and qualitative data analysis, correlation testing, regression analysis, normalisation techniques, and data modelling methods essential for research and experimentation. Through the Intelligent Decision Support Systems module, students explore technologies that assist decision-making in business, healthcare, and technology sectors, learning about data mining, classification methods, knowledge management, and the design of computerised decision support solutions for real-life challenges. The Artificial Intelligence Ethics and Applications module examines the use of AI and data science in areas such as chatbots, virtual assistants, medical diagnosis, biometric recognition, fraud detection, personalised services, and autonomous systems while analysing the ethical, social, and security implications associated with these technologies. Research Methods prepares students for independent academic and professional investigations by developing skills in research design, data collection, evaluation techniques, literature review, and research ethics. The programme concludes with a substantial Computing Masters Project, where students undertake an individual research or industry-focused project resulting in the development of software, tools, systems, or research outputs. Through presentations, demonstrations, and academic reporting, students gain valuable experience that prepares them for careers in artificial intelligence, machine learning, data analytics, research, and advanced technology industries.