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DSA 406 Exploratory Data Analysis for Big Data

¶Ù³§´¡Ìý406ÌýÌýExploratory Data Analysis for Big DataÌýÌý(1 credit hours)ÌýÌý

Exploratory data analysis (EDA) focuses on summarizing the main characteristics of data sets, often using visualization methods. The goal is not formal modeling or hypothesis testing, but understanding and exploring data to formulate hypotheses for further investigation. Students will use techniques of EDA and generalize those approaches to large data sets. Prerequisite skills and knowledge: Students should enter the course with some basic programming experience, such as experience using and familiarity with R or Python.

Typically offered in Fall, Spring, and Summer

Participatory Sciences (Certificate)

/graduate/interdisciplinary/participatory-sciences/

...Artificial Intelligence 3 DSA 405 Data Wrangling and Web Scraping 1 DSA 406 Exploratory Data...