Machine Learning for Musicians

This course introduces students to the world of music and machine learning, a key component of artificial intelligence (AI), which is revolutionizing the music industry. Through immersive exploration and hands-on projects, students will discover how advanced AI systems can interpret and enhance the music-making process, from composition to production and beyond. Through their experience, students will learn to craft innovative solutions and applications that bridge the gap between technology and artistry.

Students will engage in laboratory exercises and collaborative projects that combine technical and creative elements. Early in the semester, students will present their findings on the intersection of music and machine learning, fostering a culture of shared learning and inspiration. The curriculum also features two projects in which students will apply their skills to create machine learning-based musical applications and innovative AI applications in music, respectively. These projects, alongside continuous documentation and reflection using tools like Jupyter Notebook and GitHub, are designed to mimic the fast-paced, collaborative environment of tech start-ups, preparing students for real-world applications in music and AI.

Upon completing this course, students will possess the skills to take music and machine learning projects from concept to launch. These projects include developing custom generative audio systems, neural audio plugins, and tools for mixing and mastering. The hands-on projects will equip students with the skills and knowledge necessary to innovate and excel in a competitive music industry that is increasingly focused on AI and innovation. This course opens doors to several exciting job opportunities, including, but not limited to, Music Data Scientists, AI Audio Engineers, AI Music Producers, Interactive Music Application Developers, and Music Technology Researchers.