Data Science Ethics with R

About 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.

What you will 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