ENV HLT 211

Machine Learning for Public Health

Environmental Health Sciences · 4 units · Graduate courses (200-299)

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Project-centric introduction to concepts and applications of machine learning in public health. Students gain hands-on experiences in developing machine-learning models for various applications in public health, including exposure assessment modeling, multiomics, computational toxicology, and disease prediction.

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
Requisite: Biostatistics 100 or 201A or other introductory statistics course. Recommended preparation: environmental health courses and prior coding experience.

BruinTree reads · Prerequisite

confidence 1.00 · from UCLA’s structured data

one of

BruinTree reads · Recommended

needs reviewconfidence 0.00 · from text

BruinTree could not read this requirement — see UCLA’s wording above.

· could not read "environmental health courses" (no course number found)
· could not read "prior coding experience" (no course number found)
· no course reference could be read from this requisite

Requires

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

ENV HLT 211

BIOSTAT 100Introduction to Biostatistics
BIOSTAT 201AIntroduction to Biostatistics

2 direct requisites. The whole upstream is here — 2 courses over 1 level. Every course here opens its own tree.

Unlocks

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.