Teaching

This page contains the syllabus, lecture slides, problem sets, and/or handouts for various courses that I have taught. I do not distribute bulk solutions to my problem sets, but if you have worked one of the problems out and want to check the solution, contact me. Many problems in the problem sets are former exam questions. Feel free to use any of these materials to study or teach. Some of the figures in the slides are taken from other sources and are referenced (see the corresponding syllabus for full reference).


Deep Learning (EE599, 4 units, Spring 2019, 2020)


Machine Learning I: Supervised Learning (EE559, 4 units)


Machine Learning for Engineers (EE460, 4 units)


Signals and Systems (EE301L, formerly EE301, EE202L)


Probability and Statistics (EE364 and EE503 (formerly EE464))


Digital Communications and Coding Systems (EE564 and old EE568)


Random Processes (EE562a – currently EE562)


Introduction to Mobile/Wireless Communications (EE535)

Note: I have not taught in a long time. See Prof. Molisch


Social Network Systems (A one-time EE599 Special Topics)


Engineering Academy (ENGR 102, joint with Prof. Gupta)