COURSE CURRICULUM

This course is designed to provide students with a comprehensive understanding of artificial intelligence and its applications in audio and music, combining theoretical foundations with practical skills. All students are required to complete a set of compulsory modules that cover essential areas of knowledge in this specialized field. The module on Artificial Intelligence for Sound and Music focuses on the application of AI techniques to audio and music data, while Digital Signal Processing for Audio Applications teaches the technical principles and methods for analyzing and manipulating sound. Emerging Audio Technologies introduces students to the latest innovations in audio hardware and software, preparing them for current and future industry challenges. Machine Learning equips students with the skills to design, train, and apply predictive models to audio data, and Scientific Python ensures proficiency in programming and computational methods essential for implementing AI solutions. Engineering Research Methods provides a foundation in research design, data analysis, and scientific inquiry, supporting students in developing robust, evidence-based approaches. The Audio Engineering Dissertation allows students to undertake an independent research project, integrating their knowledge and skills to explore a specific area of interest in depth. Together, these modules prepare graduates for careers in music technology, audio engineering, and AI-driven sound applications, equipping them to innovate and contribute effectively to the industry.