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

Prerequisites: MATH 54

Formats:
Fall: 3.0 hours of lecture, 1.0 hours of discussion, and 3.0 hours of laboratory per week
Summer: 6.0 hours of lecture, 2.0 hours of discussion, and 6.0 hours of laboratory per week

Grading Basis: letter

Final Exam Status: Written final exam conducted during the scheduled final exam period

---

Class Schedule (Spring 2025):
EECS 16A – MoWe 18:30-19:59, Pimentel 1 – Babak Ayazifar

Class Notes
*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**

Class Schedule (Fall 2025):
EECS 16A – MoWe 18:30-19:59, Pimentel 1 – Babak Ayazifar

Class Notes
READ THIS:
Fall 2025 Freshman MUST take Math 54 BEFORE taking 16A..
Fall 2024 students can take the class without Math 54 but are STRONGLY discouraged to do so.

*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:

• CS enrollment policies
• EE enrollment policies
• HKN course maps