DATA 2100: Intermediate Data Analytics

Data Analytics
Course in Data Analytics
Course Description:

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.

Course Credits:
1 course unit (c.u.)*
Term Format:
Accelerated 8-Week Term
2024 Term Offered:
Spring 2 (accelerated): Mar 18 – May 14, 2024
Fall 2 (accelerated): Oct 23 - Dec 18, 2024
DATA 1010
Synchronous Session:
Weekly synchronous session required:
Online seminars meet Thursdays from 6 - 7 p.m., ET
Course Block:

*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.


Sean Kates

  • 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


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