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Exploratory Data Analysis and Pattern Discovery

QAC 305
Spring 2019
Section: 01  
Certificates: Applied Data Science
Course Cluster: Data Analysis Minor

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 SAS) 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)(PSYC)
Past Enrollment Probability: 90% or above

Last Updated on JUL-13-2024
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