DS 395 - Special Topics in Data Science

Credits: 3

Prerequisite: Instructor consent. Exploration of a topic in data science, where students craft testable research questions and retrieve an appropriate data set to answer those research questions. Includes training in some aspect of data science and incorporates extensive independent student work, with individual projects being the key product of that work, synthesizing what you have learned in the data science minor and demonstrating mastery of core data-science skills. Topics may include causal inference for data science with directed acyclic graphs (DAGs); analysis of spatial data; or multilevel models. Data Science faculty. Offered periodically depending on faculty availability and expertise and student interest.

Winter 2022, DS 395A-01: Special Topics in Data Science: Statistics & Medicine, How a Vaccine is Born (3). Covid-19 has changed life as we know it for everyone on the planet. While we are still in the clutches of this deadly, global pandemic, we recently received a ray of medical hope in the form of several vaccines. How are vaccines developed? What are the statistical methods used to analyze their effectiveness? What can history tell us about the ethics, efficacy and quality of vaccines and their distribution? How do the current available Covid-19 vaccines compare to one another? This course will attempt to answer these questions using data science skills. Prince Nelson. Data Science faculty.