Neural Networks and Deep Learning


This course is part of the UCLA Henry Samueli School of Engineering and Applied Science (HSSEAS) Master of Science in Engineering Online (MSOL) program.  It is available only to students pre-approved by HSSEAS.  For more information please contact


About this course:

EC ENGR C247 Neural Networks and Deep Learning (Instructor: J. Kao) Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: courses 131A, 133A or 205A, and M146, or equivalent. Review of machine learning concepts; maximum likelihood; supervised classification; neural network architectures; backpropagation; regularization for training neural networks; optimization for training neural networks; convolutional neural networks; practical CNN architectures; deep learning libraries in Python; recurrent neural networks, backpropagation through time, long short-term memory and gated recurrent units; variational autoencoders; generative adversarial networks; adversarial examples and training. Concurrently scheduled with course C147. Letter grading.

Contact Us

Our team members are here to help. Hours: Mon-Fri, 8am-5pm
Ready to start
your future?
By signing up, you agree to UCLA Extension’s Privacy Policy.

vector icon of building

Corporate Education

Learn how we can help your organization meet its professional development goals and corporate training needs.

Learn More

vector icon of building

Donate to UCLA Extension

Support our many efforts to reach communities in need.

Innovation Programs

Student Scholarships

Coding Boot Camp

Lifelong Learning