AI 331 - Deep Learning I

3 Credit Hours

Deep Learning I: Foundations and Convolutional Networks. This course introduces the foundations of deep learning through artificial neural networks. Students examine perceptrons, multilayer neural networks, and optimization methods such as backpropagation and gradient descent. The course emphasizes convolutional neural network (CNN) architectures and their application to image recognition. Implementations use TensorFlow and PyTorch.
Prerequisite: “C” or better in:

AI 231 - Machine Learning Fundamentals

AND MAT 337 - Probability and Statistics

Lecture Hours: 3
Term(s) Offered: Fall