Data Cleaning with R
Academic Noncredit

Data cleaning is an incredibly important part of the data science process. This course introduces a customizable data cleaning pipeline, focusing on biomedical data from electronic health records and health survey data. In this course, you will learn how to summarize the data collection process and data dictionaries, identify and address missing values using R, handle data quality issues (such as invalid and inconsistent values) using R, reshape your data into a “tidy” format using R, and create a custom, reproducible data cleaning function in R.

This noncredit class meets with a regular University of Utah credit course. Students can purchase any assigned hardcopy textbooks through our Campus Bookstore.