Seeks to develop practical proficiency with machine learning concepts, tools, and techniques as applied to music creation, audio processing, and interactive performance. Topics include supervised and unsupervised machine learning, neural network architectures, symbolic and audio-based music generation, neural audio synthesis, AI-augmented production workflows, and gesture-driven interactive systems. Engages students with machine-learning-driven systems through hands-on projects, structured lab exercises, and critical evaluation of both commercial platforms and programmatic frameworks. Emphasizes transferable analytical skills and adaptable workflows implemented within industry-standard platforms.