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Data Science Ethics with R
This course is part of Data Science with R Specialization.
Course Cost
Free course
Beginner
Skill Level
6 Hours
Self-paced lessons
This course addresses the critical ethical responsibilities of statisticians and data scientists when working with data. Through a focused exploration of key ethical challenges, students develop essential skills to recognize, analyze, and respond to common ethical issues in the field. The course begins by examining how data visualizations can mislead audiences and teaches strategies to create more honest and accurate visual representations. Students learn to identify subtle forms of data manipulation and practice creating visualizations that convey information ethically using R. The curriculum then delves into data privacy concerns, helping students understand the fundamentals of protecting sensitive information and implementing appropriate safeguards. A significant portion of the course is dedicated to algorithmic bias, where students explore how algorithms can perpetuate or amplify existing social biases. Through case studies, readings from leading experts like Cathy O'Neil and Safiya Umoja Noble, and practical exercises in R, students gain awareness of these ethical dimensions and develop frameworks for addressing them in their professional practice. The course combines theoretical knowledge with hands-on coding practice, preparing students to approach data science with greater ethical awareness.
What you'll learn
Identify and avoid misrepresentation in data visualizations
Apply ethical principles when creating data visualizations in R
Understand fundamental concepts of data privacy and protection
Recognize situations where algorithmic bias may occur
Develop strategies to mitigate potential ethical issues in data science work
Critically assess the intent behind data collection efforts
Identify appropriate safeguards for sensitive data
Evaluate algorithms for potential sources of bias and discrimination
Skills you'll gain
This course includes:
0.7 Hours PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
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There is 1 module in this course
This course focuses on the ethical responsibilities of data scientists and statisticians when working with data. Structured as a single comprehensive module, the course explores three critical areas of data ethics. First, it examines how data visualizations can misrepresent information, teaching students to identify misleading techniques and create more honest visual representations using R. The course includes a hands-on coding session with sector and services data to demonstrate ethical visualization practices. Second, the curriculum addresses data privacy concerns, helping students understand fundamental concepts of protecting sensitive information and implementing appropriate safeguards. Finally, the course explores algorithmic bias, defining this concept and highlighting situations where algorithms may perpetuate or amplify existing social inequalities. Through readings from experts like Alberto Cairo, Cathy O'Neil, and Safiya Umoja Noble, along with practical exercises, students develop a framework for approaching data science work with greater ethical awareness.
Data Ethics
Module 1 · 6 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Data Science with R Specialization
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Frequently asked Questions
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