COURSE CURRICULUM

The course provides a comprehensive and practical understanding of modern data science, artificial intelligence, machine learning, and business analytics technologies used across industries worldwide. Students begin by developing strong foundations in data science concepts, learning how to prepare, manage, analyse, and visualise real-world datasets using relevant software tools and database technologies. The programme introduces Python programming and its applications in digital innovation, enabling students to build software solutions and develop programming skills for solving practical business and technological problems. Students gain advanced knowledge of machine learning techniques, including predictive modelling, statistical analysis, probability theory, and algorithm development, allowing them to create systems capable of learning from data and making intelligent predictions. The course also focuses on big data technologies and business intelligence, where students design and implement database and analytics solutions to meet organisational requirements while exploring data warehouses, data integration, large-scale database management, and data visualisation methods. Through the study of artificial intelligence ethics and applications, students examine how AI and data science are used in areas such as chatbots, virtual assistants, fraud detection, biometric recognition, medical diagnosis, personalised services, and autonomous systems, while critically evaluating the ethical, security, and social implications of these technologies. Interactive visualisation forms another important component of the programme, teaching students how to create dynamic and web-based visualisations using tools such as D3.js to explore multidimensional datasets and discover patterns and trends. The programme concludes with a substantial individual master's project based on commercial, industrial, or research challenges, where students conduct independent research, develop a major solution or software product, and present their findings through reports, presentations, demonstrations, and academic-style publications, preparing graduates for careers in the rapidly expanding fields of data science and artificial intelligence.