BIOSTAT 203CIntroduction to Data Science in Python
Biostatistics · 4 units · Graduate courses (200-299)
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.
Requisites
Official UCLA wording
Requisites: courses 203A, 203B, 212A.
BruinTree reads · Prerequisite
confidence 1.00 · from UCLA’s structured dataRequires
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 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.