DS BMED 200
Foundations of Data Science
Data Science in Biomedicine · 4 units · Graduate courses (200-299)
Study offers background in mathematical and engineering foundations that are building blocks of data science. Topics include linear algebra, probability, and statistics. Overview of science software engineering and reproducibility fundamentals including working on a compute cluster, pipeline development, virtual notebooks, version control.
Letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Preparation: familiarity with programming and algorithms, probability, statistics, linear algebra.
BruinTree reads · Preparation
needs reviewconfidence 0.00 · from textBruinTree could not read this requirement — see UCLA’s wording above.
- · could not read "familiarity with programming" (no course number found)
- · could not read "algorithms" (no course number found)
- · could not read "probability" (no course number found)
- · could not read "statistics" (no course number found)
- · could not read "linear algebra" (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.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
DS BMED 200
- DS BMED 205Machine Learning Applications in Biomedicine
- DS BMED 206Advanced Machine Learning Applications in Biomedicine
- DS BMED 207Data Science for Medical Imaging
- DS BMED 208Recent Research in Machine Learning in Medicine
- DS BMED 209Recent Research in Data Science in Genomic Medicine