This course highlights the ethical responsibilities we have as statisticians and data scientists when working with data. This course demonstrates situations where ethical concerns with data arise and helps train our brains to be more aware of how data are used and the intent behind data collection. By the end of this course, you will be able to identify misrepresentation in visualizations, describe the basics of data privacy, and recognize potential situations where algorithmic bias is at play.
Data Science Ethics with R
Data Science Ethics with R
This course is part of Data Science with R Specialization
Instructors: Mine Çetinkaya-Rundel
Sponsored by Louisiana Workforce Commission
Gain insight into a topic and learn the fundamentals.
Beginner level
No prior experience required
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Critically assess ethical concerns considering data intent and data privacy
Identify strategies that can be incorporated to help secure sensitive data
Define algorithmic bias and become conscious of when these situations may occur
Details to know
Shareable certificate
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Assessments
1 assignment
Taught in English
Recently updated!
December 2024
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This course is part of the Data Science with R Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There is 1 module in this course
Data ethics is an essential component for those who work with data. In this module, we will become aware and hold discussions around how data visualizations can mislead and strategies to mitigate these types of situations. Further, we will discuss and critically think about data privacy. Lastly, we will define algorithmic bias and be aware of situations where this type of bias can occur.
What's included
5 videos15 readings1 assignment2 discussion prompts1 plugin
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