Global Certificate in Music & Audio AI Frontiers
-- ViewingNowThe Global Certificate in Music & Audio AI Frontiers is a comprehensive course designed to empower learners with the essential skills needed to thrive in the rapidly evolving music and audio AI industry. This course highlights the importance of AI in music and audio, covering topics such as music information retrieval, generative models, and intelligent music production.
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โข Introduction to Music & Audio AI – Overview of the intersection of music, audio, and artificial intelligence, including key concepts and use cases.
โข Data Preparation for Music & Audio AI – Techniques for preparing and processing music and audio data for machine learning.
โข Audio Feature Extraction – Methods for extracting meaningful features from audio data for machine learning tasks, such as mel-frequency cepstral coefficients (MFCCs) or chroma features.
โข Deep Learning Models for Music & Audio – Exploration of various deep learning architectures and techniques for music and audio applications, such as convolutional neural networks (CNNs) or recurrent neural networks (RNNs).
โข Generative Music and Audio Models – Overview of generative models for music and audio, including variational autoencoders (VAEs) and generative adversarial networks (GANs).
โข Music Information Retrieval – Techniques for extracting information from music, such as genre classification, tempo estimation, and beat tracking.
โข Audio Source Separation – Methods for separating audio signals into individual sources, such as vocals, drums, or other instruments.
โข Applications of Music & Audio AI – Real-world applications of music and audio AI, including music generation, recommendation, and synthesis.
โข Ethical Considerations in Music & Audio AI – Discussion of ethical considerations and potential biases in the development and deployment of music and audio AI systems.
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