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CS92PROD
Exploratory Data Analysis and Pattern Discovery

QAC 305
Spring 2021
Section: 01  
Course Cluster and Certificates: Applied Data Science Certificate

The course introduces the theory and practice of exploring, describing, summarizing and detecting patterns of interest in complex datasets. Various approaches including aggregation, clustering, data visualization, and latent variable modeling will be employed. This course will give students an opportunity to develop computational skills (primarily in R) and to learn how to discover and interpret relationships in unstructured observational data. The applications and examples for this course will be broad and relevant to many fields of study.
Credit: 1 Gen Ed Area Dept: NSM QAC, SBS QAC
Course Format: Lecture / DiscussionGrading Mode: Graded
Level: UGRD Prerequisites: QAC211 OR ECON300 OR GOVT367
Fulfills a Major Requirement for: (CADS)(DATA-MN)
Past Enrollment Probability: 75% - 89%

Last Updated on SEP-30-2020
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