COURSE CURRICULUM

The Music and Data Science MA combines advanced study in music with practical and theoretical training in data science, preparing students to work at the intersection of creativity and technology. The program equips students with a strong foundation in programming, data analysis, and machine learning, enabling them to apply these skills in music-related contexts. Core modules cover data mining and text analytics, teaching students how to implement and evaluate systems for information retrieval and analysis, as well as programming for data science to build a robust computational skillset. Students also study the theoretical and practical aspects of data science, machine learning methodologies, and their application in business and music contexts, including classical and advanced techniques such as deep learning. Music-specific modules explore music and music data history, using large datasets to investigate trends in publishing, concert attendance, genre evolution, and historical music practices. The program culminates in a major project where students apply their data science knowledge to real-world challenges in collaboration with industry partners. Optional modules provide additional opportunities to specialise in areas such as the contemporary recording industry, music monetisation, or independent research projects. Overall, the course develops interdisciplinary expertise, combining analytical, technical, and creative skills to prepare students for careers in music technology, analytics, research, and related fields.