This course introduces neural network applications for audio processing. Learn about specific features of audio data and the need for a dedicated encoder. See examples of convolutional and recurrent neural networks. Get a glimpse of the fundamental building blocks of a neural network and their significance. You'll learn how to access neural network models from the Wolfram Neural Net Repository, build an audio classifier from scratch and understand the concept of "network surgery" for adapting a pre-defined network to use for audio analysis as well as for extracting data from a network for analysis and gaining insights. Finally, the technique of transfer learning is demonstrated for approaching complex problems.