BIOSTAT 203C

Introduction to Data Science in Python

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

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Introduction to data science tools in Python. Topics include Python programming, Jupyter Notebook for literate programming, NumPy and SciPy for scientific computing, pandas for data analysis and manipulation, Matplotlib and other libraries for data visualization, scikit-learn for machine learning, and deep learning libraries.

S/U or letter grading.

When it runs

Spring 2026
Spring 2027

Scheduled, not typical — from UCLA’s Schedule of Classes, which publishes Fall 2025 through Spring 2027 and nothing before it.

Checking the Schedule of Classes…

Requisites

Official UCLA wording
Requisites: courses 203A, 203B, 212A.

BruinTree reads · Prerequisite

confidence 1.00 · from UCLA’s structured data

all of

Requires

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

BIOSTAT 203C

BIOSTAT 203AIntroduction to Data Management and Statistical Computing
BIOSTAT 203BIntroduction to Data Science in R
- BIOSTAT 203AIntroduction to Data Management and Statistical Computinganother path to it
BIOSTAT 212AStatistical Learning A

3 direct requisites. The whole upstream is here — 4 courses over 2 levels. Every course here opens its own tree.

Unlocks

What this course is a requisite for, and what those courses lead to in turn.

BIOSTAT 203C

BIOSTAT 218Observational Health Data Science and Informatics

1 course lists this as a requisite. The whole downstream is here — 1 course over 1 level. Every course here opens its own tree.