BIOSTAT 273

Machine Learning

Biostatistics · 4 units · Graduate courses (200-299)

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Covers theoretical underpinnings and practical applications of modern machine-learning and other data-intensive algorithms, including support vector machines and random forest algorithms. Students learn to download and use variety of software tools that are available for free on web.

S/U or 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.

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Requisites

Official UCLA wording
Requisites: course 200C and Mathematics 115A.

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Requires

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

BIOSTAT 273

BIOSTAT 200CMethods in Biostatistics C
MATH 115ALinear Algebra
- MATH 33ALinear Algebra and Applications
  - MATH 3BCalculus for Life Sciences Students1 more beneath
  - MATH 31BIntegration and Infinite Series1 more beneath
  - MATH 32ACalculus of Several Variables

2 direct requisites. Showing 6 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.