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

Prerequisites: EECS 16A and EECS 16B, or consent of instructor.

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

Formats:
Fall: 3 hours of lecture and 1 hour of discussion per week
Spring: 3 hours of lecture and 1 hour 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 (Fall 2024):
EECS 127/227AT – TuTh 09:30-10:59, Haas Faculty Wing F295 – Somayeh Sojoudi
Class homepage

Class Schedule (Spring 2025):
EECS 127/227AT – TuTh 12:30-13:59, Lewis 100 – Thomas A Courtade

Related Areas:

• Control, Intelligent Systems, and Robotics (CIR)