2025 Fall
EECS 16A 109L - LAB 109L
Formerly Electrical Engineering 16A
Foundations of Signals, Dynamical Systems, and Information Processing
Class #:29595
Units: 4
Instruction Mode:
In-Person Instruction
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
48
Enrolled: 0
Waitlisted: 0
Capacity: 48
Waitlist Max: 25
No Reserved Seats
Hours & Workload
3 hours of instructor presentation of course materials per week, 5 hours of outside work hours per week, 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.
Course Catalog 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.
Rules & Requirements
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials