COURSE CURRICULUM

The first year of the MSc in Natural Language Processing combines core and optional modules to provide a comprehensive education in both the theoretical and practical aspects of NLP. Core modules include Machine Learning for NLP (CMT122, 20 credits), which develops the foundational skills required to design and implement machine learning models tailored to text data, and Advanced Topics in NLP (CMT227, 20 credits), which explores recent developments and state-of-the-art techniques in the field. Computational Data Science (CMT309, 20 credits) equips students with data analysis and programming skills essential for handling large-scale text datasets, while Computational Linguistics (CMT318, 20 credits) focuses on the linguistic principles underpinning NLP systems. The NLP Dissertation (CMT405, 60 credits) allows students to undertake an independent research project, applying their skills to a real-world or research-focused problem, fostering critical thinking and technical expertise. Optional modules provide opportunities for students to specialise further, with courses such as Distributed and Cloud Computing, Human Centric Computing, Automated Reasoning, Data Visualisation, and Databases and Modelling, allowing students to develop additional computational, analytical, and engineering skills. Collectively, the program equips graduates with the expertise to pursue careers in NLP and AI across a wide range of industries or to continue into advanced research, combining technical proficiency with critical and applied understanding of text-based data.