SOCIOL 208CMachine Learning for Social Scientists
Sociology · 4 units · Graduate courses (200-299)
Conceptual, mathematical, and computational foundations of machine learning, with special focus on social science applications. Survey of supervised and unsupervised methods, including Naïve Bayes, k-means, logistic regression, decision trees (classification and regression), topic models, and neural networks. Practicalities of implementation on range of data types.
S/U or letter grading.
When it runs
Not on the schedule for any of Fall 2025 through Spring 2027. UCLA publishes only that window, so this does not mean the course is gone — check the official listing.
Requisites
Official UCLA wording
Requisites: courses 210A, 210B, or consent of instructor.
BruinTree reads · Prerequisite
needs reviewconfidence 0.55 · from text- all of
- consent of instructor
- · mixed comma-level AND/OR in "courses 210A, 210B, or consent of instructor" — grouping is a best reading
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
SOCIOL 208C
- SOCIOL 210AIntermediate Statistical Methods I
- SOCIOL 210BIntermediate Statistical Methods II
2 direct requisites. The whole upstream is here — 2 courses 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.