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CJS 310 Crime Prediction Using Open Data 3.0 Credits

Information technologies have increased the amount of data researchers and practitioners have at their disposal for analysis. This data is valuable for predicting criminal behavior and the criminogenic factors present in certain geographical areas. These predictions are in turn used to support everything from policy decisions to sentencing guidelines. This course will examine the tools used for crime prediction and the impact of their use on individuals and communities. Students will learn the logic behind the algorithms used for crime prediction so they can understand the ethical implications of crime prediction tools and methodologies. We will learn R through edX so we have some hands on knowledge of one of the post popular tools being used in data science – focused on criminal justice.

College/Department: College of Arts and Sciences
Repeat Status: Not repeatable for credit
Prerequisites: CJS 270 [Min Grade: C-] and CJS 250 [Min Grade: C-]

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