DS BMED 219

Data Science Algorithms in Biomedicine

Data Science in Biomedicine · 4 units · Graduate courses (200-299)

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Development and application of algorithmic approaches to problems in biomedicine, with focus on formulating interdisciplinary problems as computational problems and then solving these problems using algorithmic techniques. Design, analysis, optimization, and implementation of algorithms. Topics include string algorithms in genomics and scalable machine learning algorithms applied to medical data. Satisfies capstone requirement. Students present their results.

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
Requisite: course 200 or equivalent.

BruinTree reads · Prerequisite

confidence 1.00 · from UCLA’s structured data

DS BMED 200

Requires

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

DS BMED 219

DS BMED 200Foundations of Data Science

1 direct requisite. The whole upstream is here — 1 course 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.