dotsdots
🎉
Enrollment Open!
Data Cleaning with R
headshot of the course developer

Developed by Rebecca Barter

Data rarely arrives in an analysis-ready format. The process of molding a dataset so that it is well-suited for analysis is known as “data cleaning”. Data cleaning is an incredibly important part of the data science process. Not only does it ensure that your data is correctly formatted for your analysis, it also provides you with a clear understanding of how real-world information is represented in your data, as well as its limitations. This course introduces a customizable data cleaning pipeline, focusing on biomedical data from electronic health records and health survey data. Learn how to utilize the R programming language, and it is assumed that learners have taken our “Introduction to R for Data Analysis” course, or equivalent. It is recommended that learners have also taken our “Advanced R for Data Analysis” course, but this is not a requirement.
Open Enrollment
Self-Paced
6 Skills Developed
Online, Self-Paced
$149
Enroll Now
A monitor with a light bulb coming out of it

What you'll learn

1
You need to critically evaluate and enhance the quality of your data, an essential task for turning raw data into reliable insights.
2
You want to learn how to prepare your data for a variety of analyses
3
You aspire to streamline your data science workflow in R, making your processes more transparent, reproducible, and effective.

Supported Careers

Get ready to excel in these roles after taking this program

  • Financial Analyst
  • Data Scientist:
  • Healthcare Data Analyst:
  • Healthcare Administrator
Stacked papers

Includes

6 skills developed
Hands-on projects to apply learnings
Project visibility to hiring managers
Real feedback from moderators
Insights into your skill gaps
Portfolio artifacts to keep forever

Skills Developed

Some of the exciting skills you will develop through the experience

  • Data Documentation & Data Management
  • Column Names
  • Missing Values
  • Invalid & Inconsistent Values

About the skill experiences

Reformat your data for analysis

Gain experience with techniques for reformatting your data, making it easier to analyze and visualize

Enhance your R coding skills

Gain confidence working with messy real-world datasets in R

Uncover and address data quality issues

Learn how to identify and address data quality issues

Build reproducible data cleaning workflows

Learn how to use R to create and apply a customizable and reproducible data cleaning procedure to prepare any dataset for analysis

Become visible to Hiring Managers with Headlamp

This course lets you build portfolio artifacts alongside our expert instructors. Headlamp shares your portfolio with Hiring Managers looking for your new skill.
Headlamp logo with success examples

About the Skill Experience Developers:

headshot of the course developer

Rebecca Barter

Dr Barter is a Research Assistant Professor at the University of Utah. She is a programmer, data scientist, and statistician with over a decade of experience practicing and teaching data science. She is the co-author of the book “Veridical Data Science: The Practice of Responsible Data Analysis and Decision Making” (www.vdsbook.com) and the author of a popular data science blog (www.rebeccabarter.com).

How Headlamp Works
    Master a most-wanted skill
    Dive into a skill that’s at the top of every Employer’s list. Headlamp makes learning easy with interactive modules and 100% human-support.
    Build a portfolio
    Stand out by documenting your journey through any path. We’ll help you craft a portfolio alongside our expert instructors.
    Get matched with Employers
    Headlamp showcases your portfolio to eager Employers, making entry into the job market as smooth as possible.