DA 302WPredictive Analytics
DA 302W is a four-credit course with lecture and writing components. (DA201W, DA 302W , and DA 401W each carry only one credit of "writing"; completion of all three courses is required to meet the writing requirement.) The principal objective of this course is to help students predict ¿what will happen¿ in future events based on historical data. This course exposes students to predictive analytics techniques that are consistent with best practices in the data analytics industry. Students will learn how to properly examine problem contexts to use the most appropriate method to develop the best predictive model. Students will also learn how to evaluate their results and interpret findings to users at different levels of an organization. This course focuses on the application of spreadsheets, scripting languages for data analytics, and current statistical software packages.
Prerequisites
You need one from each line:
Where it sits in degree plans
Suggested plans most often put it in Year 2 · Spring (1 program).
Required in (1)
- Functional Data Analytics, B.S.