MATH 118
Mathematical Methods of Data Theory
Mathematics · 4 units · Undergraduate upper division (100-199)
Introduction to computational methods for data problems with focus on linear algebra and optimization. Matrix and tensor factorization, PageRank, assorted other topics in matrices, linear programming, unconstrained optimization, constrained optimization, integer optimization, dynamic programming, and stochastic optimization.
P/NP or letter grading.
Requisites
Official UCLA wording
Requisites: courses 42, 115A.
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
MATH 118
- MATH 42Introduction to Data-Driven Mathematical Modeling: Life, Universe, and Everything
- MATH 31ADifferential and Integral Calculus
- MATH 1Precalculus
- MATH 31BIntegration and Infinite Series
- COMPTNG 10AIntroduction to Programming
- MATH 32ACalculus of Several Variables
- MATH 115ALinear Algebra
- MATH 33ALinear Algebra and Applications
2 direct requisites. Showing 24 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 118
- MATH M148Experience of Data Science
- STATS M148Experience of Data Science
2 courses list this as a requisite. The whole downstream is here — 2 courses over 1 level. Every course here opens its own tree.