DA 535 Introduction to Deep Learning

This course offers an introduction of the fundamental concepts in Deep Learning, a subfield of machine learning that uses neural networks to model and solve complex problems. Deep Learning has emerged as a powerful technology with diverse applications across various domains. The course also covers a wide range of topics, including Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Encoder-Decoder Models, Reinforcement Learning (RL), Transformers, and Generative Adversarial Networks (GANs). Upon completing the course, students are expected to acquire the skills and knowledge necessary to address real-world challenges using deep learning techniques.

Credits

3

Cross Listed Courses

CSC 435 & CSC 535 & DA 535

Prerequisite

Open to students who have earned credit for DA 501 and DA 515; however, students who have taken CSC 416/516 or DA 516 cannot take this course