Catalog Course Description

This course offers an introduction to signals, systems, optimization, controls, and machine learning, all grounded in linear algebraic techniques. After a brief review of linear algebra, students will delve into topics such as signal processing, linear systems, feedback control, optimization methods, and foundational machine learning algorithms. Emphasizing practical applications, the course prepares EECS majors for advanced study by connecting mathematical concepts to real-world engineering problems.

Summer Term

2 hours of The exchange of opinions or questions on course material per week and 6 hours of Instructor presentation of course materials per week and 10 hours of Outside Work Hours per week and 6 hours of Instructional experiences requiring special laboratory equipment and facilities per week.

Fall Term

3 hours of Instructor presentation of course materials per week and 5 hours of Outside Work Hours per week and 3 hours of Instructional experiences requiring special laboratory equipment and facilities per week and 1 hours of The exchange of opinions or questions on course material per week.

Electrical Engineering 16A