COM SCI M148
Introduction to Data Science
Computer Science · 4 units · Undergraduate upper division (100-199)
(Same as Electrical and Computer Engineering M148 and Chemical Engineering 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.
Requisites
Official UCLA wording
Requisites: course 31 or Program in Computing 10A, and 10B, and one course from Civil and Environmental Engineering 110, Electrical and Computer Engineering 131A, Mathematics 170A, Mathematics 170E, or Statistics 100A.
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.
COM SCI M148
- COM SCI 31Introduction to Computer Science I
- C&EE 110Introduction to Probability and Statistics for Engineers
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
COM SCI M148
- COM SCI 163Deep Learning for Computer Vision
1 course lists this as a requisite. The whole downstream is here — 1 course over 1 level. Every course here opens its own tree.