MATH 164

Optimization

Mathematics · 4 units · Undergraduate upper division (100-199)

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Not open for credit to students with credit for former Electrical Engineering 136. Fundamentals of optimization. Linear programming: basic solutions, simplex method, duality theory. Unconstrained optimization, Newton method for minimization. Nonlinear programming, optimality conditions for constrained problems. Additional topics from linear and nonlinear programming.

P/NP or letter grading.

Requisites

Official UCLA wording
Enforced requisites: courses 115A, 131A.

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Requires

Everything that has to come before this course, not just the courses named in the requisite above.

MATH 164

MATH 115ALinear Algebra
- MATH 33ALinear Algebra and Applications
  - MATH 3BCalculus for Life Sciences Students1 more beneath
  - MATH 31BIntegration and Infinite Seriesanother path to it
  - MATH 32ACalculus of Several Variablesanother path to it
MATH 131AAnalysis
- MATH 32BCalculus of Several Variables
  - MATH 31BIntegration and Infinite Series1 more beneath
  - MATH 32ACalculus of Several Variables1 more beneath
- MATH 33BDifferential Equations
  - MATH 31BIntegration and Infinite Series

2 direct requisites. Showing 11 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.

Unlocks

What this course is a requisite for, and what those courses lead to in turn.

MATH 164

MATH 156Machine Learning
- MATH M148Experience of Data Science
- STATS 147Data Technologies for Data Scientists
- STATS M148Experience of Data Science
- STATS C163Generative Data Science
- STATS 184