BIOSTAT 212A
Statistical Learning A
Biostatistics · 4 units · Graduate courses (200-299)
(Formerly numbered 212.) Elements of statistical learning. Topics include linear regression, classification (logistic regression, discriminant analysis), resampling methods (cross-validation, bootstrap), model selection (subset, stepwise) and regularization (ridge, lasso).
Letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Requisite: course 100A.
BruinTree reads · Prerequisite
needs reviewconfidence 0.90 · from UCLA’s structured data- · "BIOSTAT 100A" is not in this catalog version
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
BIOSTAT 212A
- BIOSTAT 203CIntroduction to Data Science in Python
- BIOSTAT 218Observational Health Data Science and Informatics
- BIOSTAT 212BStatistical Learning B
2 courses list this as a requisite. The whole downstream is here — 3 courses over 2 levels. Every course here opens its own tree.