DSE 406 Deep Learning and Generative AI

Credits: 3

This course covers Deep Learning foundations, including neural networks, model validation, and hyperparameter optimization. Topics include MLPs, Autoencoders, CNNs, RNNs, LSTMs, and Transformers. Applications span image classification, regression, time-series, NLP, text/image generation, and AI ethics. Hands-on projects and case studies equip students to design, implement, and evaluate AI systems.

Prerequisites: CSC 215, MATH 315, and MATH 381
Notes: This course is cross-listed with CSC 406 and DSE 506.

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