EPIDEM 410
Introduction to Python for Epidemiologists
Epidemiology · 2 units · Graduate professional courses (400-499)
Introduction to use of Python programming language for epidemiologic analyses of big data. Topics covered include supervised and unsupervised learning methods, feature engineering, and model evaluation approaches using both quantitative and text-based health data.
S/U or letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Requisites: Biostatistics 100A, Public Health 200A.
BruinTree reads · Prerequisite
needs reviewconfidence 0.80 · from text- · "BIOSTAT 100A" is not in this catalog version
- · "PUB HLT 200A" 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.
EPIDEM 410
- EPIDEM 404Advanced SAS Techniques for Management and Analysis of Epidemiologic Data
1 course lists this as a requisite. The whole downstream is here — 1 course over 1 level. Every course here opens its own tree.