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.
Questions? Call Academic Programs at 801-585-9963 or use our online form.
Class Sections For Data Cleaning with R (CC 110)
Fall 2026 Section 90, Starting on: 10/19/2026
| Date(s) | Day | Time | Location |
|---|---|---|---|
| 10/19/26 - 12/10/26 | Online |
Instructor: TINGYING HE
Spring 2027 Section 90, Starting on: 03/03/2027
Students are able to earn a badge by completing more than one course in a designated series. Projects within each course will be graded for competency. This program is a partnership between The University of Utah's Kahlert School of Computing and University Connected Learning. For more, visit: https://continue.utah.edu/proed/biotech
| Date(s) | Day | Time | Location |
|---|---|---|---|
| 03/03/27 - 04/27/27 | Online |
Instructor: TINGYING HE
Registration begins on Nov 05, 2026You might also like:
Questions? Call Academic Programs at 801-585-9963 or use our online form.
