Ethical Frameworks in Data Science

As data-driven systems increasingly shape our daily lives, from healthcare outcomes to internet recommendations, understanding the moral implications of these technologies is essential. This course introduces the foundational principles required to build and use data systems responsibly in a modern digital landscape. You will develop the skills to recognize potential harms and implement ethical safeguards throughout the data lifecycle. What you'll learn: - Understand the core terminology and philosophical foundations of data ethics. - Identify and mitigate algorithmic bias in machine learning and automated systems. - Analyze the ethical implications of data privacy, surveillance, and digital security. - Apply responsible AI principles to real-world scenarios in healthcare and technology. - Explore modern concepts of algorithmic transparency and data governance. - Evaluate the social impact of large-scale data collection and processing. The course begins with essential definitions and ethical theories before moving into practical applications and contemporary case studies. It is designed for beginners who want to understand the societal impact of technology, with no technical prerequisites required. Begin your journey toward becoming a responsible data professional.