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.

Units: 4

Also Offered As: ELENG 66

Prerequisites: MATH 54

Grading Basis: Default Letter Grade; P/NP Option

Final Exam Status: Yes

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Class Schedule (Fall 2026):
EE 66 – MoWe 18:30-19:59, Pimentel 1 – Babak Ayazifar

Class Notes
PLEASE READ: Math 54 or Phyiscs 89 is an enforced prerequsite for this course. Students cannot enroll unless they have fulfilled this requirement.

Reserve groups will expire during the adjustment period.

*To enroll in this class, select the lecture and the 999 (placeholder) discussion and 999L (placeholder) Lab sections. Assignment to the actual sections will be managed by teaching staff.*

**Enrollment Permission seats are reserved for internal programs and are not open. Please DO NOT email the instructor or scheduling to request a seat**

Links:

• EECS Course Archives (CalNet authentication required)
• CS enrollment policies
• EE enrollment policies
• HKN course maps