ECE 398 PROGRAM METHODS FOR MACHINE LEARNING
Description: This course will introduce auto-differentiation tools like PyTorch, basic machine learning algorithms (including linear regression, logistic regression, deep nets, k-means clustering), and extend them with custom extensions to fit your needs. Auto-differentiation tools are one of the most important tools for data analysis and a solid understanding is increasingly important in many disciplines. In contrast to existing courses that focus on algorithmic and theoretical aspects, here we focus on studying material that permits deploying auto-diff tools to your area of interest.
ECE 329 FIELDS AND WAVES I
2020 Spring; 2020 Fall; 2021 Spring
Description: Fundamentals of electromagnetic fields and waves and their engineering applications: static electric and magnetic fields; energy storage; Maxwell’s equations for time-varying fields; wave solutions in free space, dielectrics and conducting media, transmission line systems; time- and frequency-domain analysis of transmission line circuits and Smith chart applications. Course Information: Prerequisite: ECE 210.
ECE 110 INTRODUCTION TO ELECTRONICS
2019 Spring; 2019 Fall
Description: Introduction to selected fundamental concepts and principles in electrical engineering. Emphasis on measurement, modeling, and analysis of circuits and electronics while introducing numerous applications. Includes sub-discipline topics of electrical and computer engineering, for example, electromagnetics, control, signal processing, microelectronics, communications, and scientific computing basics. Lab work incorporates sensors and motors into an autonomous moving vehicle, designed and constructed to perform tasks jointly determined by the instructors and students.