Dec 05, 2022  
2017-2018 Undergraduate Bulletin 
    
2017-2018 Undergraduate Bulletin [ARCHIVED CATALOG]

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MGMT 362 - Business Data Analytics


Credit(s): 3
Lecture: 3
Non-Lecture: 0
This course aims to provide an applied overview of business data analytics methods such as Generalized Additive Models, Decision Trees, Boosting, Bagging, Neural Networks and Support Vector Machines as well as more classical linear approaches such as Logistic Regression, and Nearest Neighbors. Computing is done in R, and students will focus on how the techniques covered can be applied to solving business problems. Restricted to School of Business majors. Offered every Spring.

Prerequisite(s): ECON 305 /MGMT 305  and junior standing.



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