COM SCI 247 · CS 247Advanced Data Mining
Computer Science · 4 units · Graduate courses (200-299)
Introduction of concepts, algorithms, and techniques of data mining on different types of datasets, covering basic data mining algorithms, advanced topics on text mining, recommender systems, and graph/network mining. Team-based project involving hands-on practice of mining useful knowledge from large data sets is required.
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
Requisite: course 145 or M146 or equivalent.
BruinTree reads · Prerequisite
needs reviewconfidence 0.50 · from text- COM SCI 145
- COM SCI M146
- equivalent
- · could not read "equivalent" (no course number found)
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
COM SCI 247
- COM SCI 145Introduction to Data Mining
- COM SCI 32Introduction to Computer Science II
- COM SCI 31Introduction to Computer Science I
- COM SCI M146Introduction to Machine Learning
- C&EE 110Introduction to Probability and Statistics for Engineers
- COMPTNG 10CAdvanced Programming
- EC ENGR 131AProbability and Statistics
- MATH 33ALinear Algebra and Applications
- STATS 100AIntroduction to Probability
- MATH 170AProbability Theory I
- MATH 131AAnalysis
- MATH 170EIntroduction to Probability and Statistics 1: Probability
2 direct requisites. Showing 26 courses over 3 levels; the branches marked with a count carry on past it. 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.