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DATA 250. Fundamentals of Data Science. 1 Credit.

Offered Either Fall or Spring; Lecture hours:3
An introduction to the concepts, core techniques and software of data science; emphasizing both data science principles and methods. Topics may include: computational libraries for data science and visualization; statistical and machine learning algorithms for regression, classification and clustering. Prerequisites: CSCI 204 and MATH 216 or MATH 227.

Data Science

https://coursecatalog.bucknell.edu/collegeofartsandsciencescurricula/areasofstudy/datascience/
Data science is a growing field that can be used to reveal insight into authorship of old texts, assist in personalized health care, predict future epidemics, understand customer behavior and provide business insight, quantify and predict effects of climate change, and improve automation via tools like computer vision. On our campus, data science can be used to study food insecurity, final exam scheduling, housing and traffic flow. This wide variety of applications is what makes data science so important.