COURSE CURRICULUM

This Artificial Intelligence programme provides students with advanced knowledge and practical expertise in artificial intelligence, machine learning, data analytics, and intelligent systems development, preparing them for careers in a wide range of technology-driven industries. The course begins with Artificial Intelligence Foundations, where students develop an understanding of key concepts including knowledge representation, reasoning, algorithms, problem solving, planning, and the creation of AI applications. Students further strengthen their technical capabilities through the Machine Learning module, which focuses on predictive modelling, learning algorithms, probability theory, statistical methods, and inference techniques that enable systems to learn from data and make intelligent decisions without explicit programming. Statistical Methods for Data Analytics equips students with practical skills in quantitative and qualitative analysis, regression, correlation testing, normalisation, and data modelling techniques essential for research and industrial applications. Through Intelligent Decision Support Systems, students learn how computerised methods such as classification, data mining, and knowledge management can support decision-making in business, healthcare, and technology environments while gaining experience in developing practical decision support solutions. The Artificial Intelligence Ethics and Applications module explores the use of AI technologies in areas including chatbots, virtual assistants, medical diagnosis, fraud detection, biometric recognition, personalised services, and autonomous systems while critically examining their ethical, social, and security implications. Research Methods develops students' abilities to conduct academic investigations, evaluate literature, generate evidence, collect and analyse data, and apply research ethics within computing projects. The programme culminates in a substantial Computing Masters Project involving independent research or industry-focused development work, resulting in a major software, system, or research output. Students may also undertake vocational or research internships, gaining valuable professional experience, research expertise, industry exposure, and enhanced employability in artificial intelligence, machine learning, data analytics, and related technology sectors.