COURSE CURRICULUM

The MSc in Artificial Intelligence and Data Science modules provide a comprehensive combination of theoretical knowledge, practical technical skills, ethical awareness, research capabilities, and industry experience. Artificial Intelligence Ethics and Applications focuses on the professional, legal, and ethical responsibilities involved in developing AI systems, including responsible computing and trustworthy AI principles, with applications in areas such as data mining, information retrieval, recommendation systems, natural language processing, social network analysis, and text mining. Artificial Intelligence Knowledge Representation and Reasoning develops advanced understanding of knowledge-driven AI, including logic, semantic and knowledge graphs, ontologies, rules, search, reasoning, intelligent agents, multi-agent systems, and nature-inspired agents. The Big Data module introduces contemporary technologies, algorithms, and practices for handling large-scale datasets, including practical experience with Apache Hadoop, Apache Kafka, Apache Spark, and Python. Data Science Elements builds essential knowledge of probability, statistics, linear algebra, data cleaning, transformation, analysis, and visualization through practical programming activities. Data Scientist Toolbox develops industry-oriented software development skills through agile methodologies, continuous integration, deployment, delivery, and software quality management tools. Deep Learning explores neural networks, training methods, modern network architectures, cloud-based computing, and practical applications of deep learning in AI solutions. Machine Learning provides a strong foundation in how computers learn from data, covering machine learning concepts, classifications, theories, and practical solution techniques. The Industrial Group Project gives students the opportunity to work collaboratively on realistic software projects supplied by industry partners, helping them apply their knowledge in professional environments and develop teamwork and software development skills. The Dissertation is an individual research project supervised by a lecturer, requiring students to develop a software solution to a real-world problem while applying knowledge gained throughout the programme and strengthening their research abilities. Research Skills and Dissertation Preparation further supports students in developing the academic and research skills necessary for successfully completing their dissertation and progressing as AI and Data Science professionals. Overall, these modules combine AI, machine learning, deep learning, data science, big data, software engineering, responsible AI, research, and practical industry experience, preparing graduates for advanced professional and research-oriented careers in AI and Data Science.