[UG] Two-unit class on Deep Learning

The following announcement is from USC Alfred E. Mann Department of Biomedical Engineering. Please contact them directly if you have any questions.

BME 499 is a two-unit class on Deep Learning for Biomedical Engineering in the fall. The pre-requisite for it is a Matlab course, but students with experience programming in other languages would be fine as well. The class will meet from 2:00-3:50 on Thursdays in the fall and does not need d-clearance from the department.

Catalogue Description

Deep neural networks, machine learning, biomedical data, microscopic and pathological image analysis and classification, convolution neural network, recurrent neural network, deep learning model

 

Course Description

Artificial intelligence with deep learning methods has demonstrated power in many biomedical engineering problems: microscopic and pathological imaging analysis and classification, sequence analysis and structure/function prediction, and more. Our goal is to introduce undergraduate biomedical engineering students to the cutting-edge development of deep neural network algorithms in the field. Through this course, students will get familiar with the python programming language and computing tools available in the field of deep learning (DL). They will learn how to apply the deep neural network (CNN and RNN) models on biomedical image and sequence analysis and develop an appreciation of DL tools.  They will also learn how to set up their own data to generate new and improved models.

BME 499 Deep Learning – Fall 2025 Syllabus

Published on April 16th, 2025Last updated on April 16th, 2025