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'll Learn
- Critically assess ethical concerns regarding data intent and privacy
- Identify strategies to secure sensitive data
- Define algorithmic bias and recognize its occurrences
Prerequisites
- Basic computer and internet skills
- Ability to read English instructions and complete short practice activities
Instructors
Mine Çetinkaya-Rundel
Associate Professor of the Practice
Dr. Elijah Meyer
Assistant Teaching Professor