STATS 231C · STAT 231CTheories of Machine Learning
Statistics · 4 units · Graduate courses (200-299)
Introduction to many useful nonparametric techniques such as nonparametric density estimation, nonparametric regression, and high-dimensional statistical modeling. Some semiparametric techniques and functional data analysis.
Letter grading.
When it runs
Not on the schedule for any of Fall 2025 through Spring 2027. UCLA publishes only that window, so this does not mean the course is gone — check the official listing.
Requisites
Official UCLA wording
Requisites: courses 200A, 231B.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
STATS 231C
- STATS 200AApplied Probability
- STATS 100AIntroduction to Probability
- MATH 170AProbability Theory I
- STATS 231BMethods of Machine Learning
- STATS 208Statistical Learning Theory
- STATS M231APattern Recognition and Machine Learning
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.
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What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.