24-789 Intermediate Deep Learning for Engineers

6 units, Carnegie Mellon University

This course will introduce some of the advances in deep learning technology such as sequential learning using Recurrent Neural Networks, Generative Adversarial Networks, Attention models and Transformers, and Diffusion models. Students will learn how to implement these models using deep learning libraries (Pytorch). Introduction to deep learning is the prerequisite.

Prerequisites: (10-715 or 10-601 or 11-785 or 24-787) and (24-788 or 11-785)

Offered: Fall 2025

Courseweave needs JavaScript to show sections, workloads and planning tools.