Advanced Certificate in Robotic Music Composition: Data-Driven
-- ViewingNowThe Advanced Certificate in Robotic Music Composition: Data-Driven course is a comprehensive program that empowers learners with the skills to create algorithmic and generative music using AI and machine learning technologies. This course is vital in today's music industry, where data-driven music composition is increasingly in demand.
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โข Advanced Music Theory: an in-depth study of music theory, including harmony, melody, and counterpoint, with a focus on how these concepts can be applied in robotic music composition.
โข Introduction to Robotic Music Composition: a unit covering the basics of robotic music composition, including the history of the field, the different types of robotic musicians, and the software and hardware required for composition.
โข Data Analysis for Music Composition: techniques for analyzing data to inform music composition, including data mining, machine learning, and statistical analysis.
โข Algorithmic Music Composition: the use of algorithms and computational processes to generate music, including the use of programming languages such as Python and Max/MSP.
โข Machine Listening for Music Composition: the use of machine learning algorithms to analyze and interpret audio data, enabling the creation of music that responds to its environment.
โข Interface Design for Robotic Musicians: the design of interfaces for controlling robotic musicians, including the use of sensors, actuators, and other input devices.
โข Sound Synthesis for Robotic Musicians: techniques for generating sound using software and hardware, including the use of physical modeling and digital signal processing.
โข Collaborative Robotic Music Composition: the development of systems for collaborative music composition involving both human and robotic musicians.
โข Evaluation and Criticism of Robotic Music: techniques for evaluating and critiquing robotic music compositions, including the use of objective and subjective metrics.
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