In Data Analytics 2100: Intermediate Data Analytics students learn the fundamentals of two skills required by many data science jobs: survey and experimental research. The course trains students in all aspects of the survey research process, including designing good survey questionnaires, drawing samples, weighting data, and analyzing survey responses. Students come away from the class with an understanding of how to design, analyze a randomized experiment, and build upon the R skills gained in previous courses.
Certificate students and individual course takers must complete a prerequisite data analytics course before enrolling in this course. Students who complete all four courses earn the Certificate in Data Analytics.
*Academic credit is defined by the University of Pennsylvania as a course unit (c.u.). A course unit (c.u.) is a general measure of academic work over a period of time, typically a term (semester or summer). A c.u. (or a fraction of a c.u.) represents different types of academic work across different types of academic programs and is the basic unit of progress toward a degree. One c.u. is usually converted to a four-semester-hour course.
- Associate Director of Programs in Data Analytics, University of Pennsylvania
Sean Kates is the Associate Director of Programs in Data Analytics at the University of Pennsylvania and teaches data sciences classes as part of Penn LPS Online’s Data Analytics Certificate and in the Fels Institute of Government. Prior to coming to Penn, Sean received a PhD in politics from New York… Read more