AI 332 - Deep Learning II

3 Credit Hours

Deep Learning II: Sequential and Advanced Architectures (RNN, GRU, LSTM). This course focuses on sequential models and advanced deep learning architectures. Students explore recurrent neural networks (RNNs), gated recurrent units (GRUs), and long short-term memory (LSTM) networks. The course also introduces attention mechanisms and sequence-to-sequence learning, with applications in time-series forecasting and speech recognition.
Prerequisite: A “C” or better in:

AI 331 Deep Learning I: Foundations and Convolutional Networks

AND MAT 334 - Differential Equations

Lecture Hours: 3
Term(s) Offered: Spring