Data science is changing our lives. While the importance of data science is widely acknowledged, there are also great concerns around it. How are data generated? How can they be used to make predictions and inform insights? What can be the potential dangers of applying data science techniques? What are the social and human implications of their uses? This multidisciplinary course explores these questions through hands-on experience on key technical components in data science and critical reviews of human and social implications in various real-world examples, ranging from social science to arts and humanities to engineering. In the course, students will 1) learn basic concepts and skills in data science (e.g., crawling and visualization); 2) apply these skills in a creative project; 3) discuss social and human implications of data science, including data privacy; algorithmic bias, transparency, fairness, and accountability; research ethics; data curation and reproducibility; and societal impacts. This course encourages students to reconsider our common-place assumptions about how data science works and be critical about the responsible use of data.

Core: Data and Discovery (Undergraduate)
4 credits – 15 Weeks