ENEE 464
Introduction to Optimization
Students will be introduced to linear, nonlinear, unconstrained, constrained optimization. Convex optimization will be highlighted. Applications will be considered, in particular in the area of machine learning. Some optimization algorithms may be discussed, time permitting.
Prerequisites & course information
Prerequisite: One of the following: ENEE290 , MATH240 , MATH341 , or MATH461 ; and must have completed or be concurrently enrolled in ENEE324 or STAT400 . Recommended: Experience in Matlab or Python. Restriction: Must be in the Department of Electrical and Computer Engineering; and must have permission of ENGR-Electrical & Computer Engineering department. Credit Only Granted for: ENEE464 or ENEE469O. Formerly: ENEE469O.
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- Introduction to Optimization · 3 Credits