EC ENGR M148 · EE M148Introduction to Data Science
Electrical and Computer Engineering · 4 units · Undergraduate upper division (100-199)
(Same as Chemical Engineering M148 and Computer Science M148.) How to analyze data arising in real world so as to understand corresponding phenomenon. Covers topics in machine learning, data analytics, and statistical modeling classically employed for prediction. Comprehensive, hands-on overview of data science domain by blending theoretical and practical instruction. Data science lifecycle: data selection and cleaning, feature engineering, model selection, and prediction methodologies.
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: one course from 131A, Civil and Environmental Engineering 110, Mathematics 170A, Mathematics 170E, or Statistics 100A, and Computer Science 31 or Program in Computing 10A, and 10B.
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.
EC ENGR M148
- EC ENGR 131AProbability and Statistics
- C&EE 110Introduction to Probability and Statistics for Engineers
- COM SCI 31Introduction to Computer Science I
- COMPTNG 10AIntroduction to Programming
- MATH 170AProbability Theory I
- MATH 131AAnalysis
- STATS 100AIntroduction to Probability
- COMPTNG 10BIntermediate Programming
- MATH 170EIntroduction to Probability and Statistics 1: Probability
8 direct requisites. Showing 29 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.