DSC622 Deep Learning and its Applications

[3–0, 3 cr.]

This course covers principles of deep learning and in its applications. Students will learn how to build and use different kinds of deep neural networks using hands-on approach. Topics include feedforward networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers and encoders/decoders. The course will include hands-on applications covering natural language processing tasks, behavioral analysis, financial analysis and anomalies detection.

Pre-requisite: DSC602 Python for Data Science and DSC605 Time Series Analysis