Catalog Description: This course offers an introduction to optimization models and their applications, ranging from machine learning and statistics to decision-making and control, with emphasis on numerically tractable problems, such as linear or constrained least-squares optimization.

Units: 4

Related Areas:

• Control, Intelligent Systems, and Robotics (CIR)

Prerequisites: MATH 54 or consent of instructor.

Credit Restrictions: Students will receive no credit for EECS 227AT after taking EECS 127 or Electrical Engineering 127/227AT.

Formats:
Fall: 3.0 hours of lecture and 1.0 hours of discussion per week
Spring: 3.0 hours of lecture and 1.0 hours of discussion per week

Grading Basis: letter

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

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Class Schedule (Spring 2026):
EECS 127/227AT – TuTh 14:00-15:29, Stanley 105 – Gireeja Vishnu Ranade

Links:

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