Data Science Ethics with R
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12 reviews
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
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There is 1 module in this course
Develop the ethical mindset every data scientist needs. In this course, you’ll examine the real-world implications of how data are collected, analyzed, and presented and the role of ethics in ensuring fairness, transparency, and trust.
Through examples and case studies, you’ll learn to recognize misrepresentation in visualizations, algorithmic bias in models, and privacy risks in data collection. You’ll also explore strategies for mitigating these challenges and communicating results responsibly. By the end of this course, you’ll be able to identify ethical risks, apply frameworks for responsible data use, and make informed choices that uphold integrity in your analyses.
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 videos17 readings1 assignment2 discussion prompts1 plugin
5 videos•Total 44 minutes
- Welcome•1 minute
- Misrepresentation•10 minutes
- Code Along :: Sectors and Services•21 minutes
- Data Privacy•5 minutes
- Algorithmic Bias•8 minutes
17 readings•Total 288 minutes
- Course Overview•10 minutes
- Meet Your Instructors•10 minutes
- Get Ready to Compute with R and RStudio!•10 minutes
- A Note about Sensitive Topics•10 minutes
- List of Citations and Sources•10 minutes
- Discussion Guidelines•10 minutes
- Report a problem with the course•5 minutes
- Code Along :: Sectors and Services - Companion•10 minutes
- Code Along :: Sectors and Services - Companion (Complete)•10 minutes
- Alberto Cairo - How Charts Lie•58 minutes
- Modern Data Science with R: Chp 8.1 - 8.5•10 minutes
- Modern Data Science with R: Chp 8.6•10 minutes
- Modern Data Science with R: Chp 8.7 - 8.11•10 minutes
- Joy Buolamwini - The Coded Gaze: Unmasking Algorithmic Bias•10 minutes
- Cathy O’Neil - Weapons of Math Destruction•60 minutes
- Safiya Umoja Noble - Imagining a Future Free from the Algorithms of Oppression•35 minutes
- Share your learning experience•10 minutes
1 assignment•Total 30 minutes
- Data Ethics Quiz•30 minutes
2 discussion prompts•Total 20 minutes
- Course Introductions•10 minutes
- Final Reflection: Data Ethics and Literacy•10 minutes
1 plugin•Total 15 minutes
- Conveying the Right Message through Visualization•15 minutes
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Reviewed on Oct 2, 2025
It is a perfect amalgamation of making you scratch your head and also holding your hand through all of the new information thrown at you.
Reviewed on Oct 17, 2025
Nice and concise course about the ethics in data science. The information in this course is appliable not only to R, but to other data science methods as well.
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