Ethics in Data Science Curriculum

This curriculum focuses on the ethical considerations and best practices in the field of data science. Understanding the ethical implications of data science is crucial for ensuring responsible and transparent use of data.

Key Topics

• Data Privacy: The importance of protecting individual privacy and handling sensitive data.
• Bias and Fairness: Addressing the issues of bias in data and algorithms and promoting fairness.
• Transparency: Ensuring that the processes and decisions made using data are understandable and accountable.
• Accountability: Establishing clear responsibility for actions and decisions made with data.
• Regulatory Compliance: Adhering to relevant laws and regulations regarding data usage.

Case Studies

• Study on Bias in Machine Learning
• Data Privacy in Healthcare

Additional Resources

• Introduction to Ethics in Data Science
• Ethical Guidelines for Data Scientists

Data Science Ethics