Data Analytics

BAAS Course Block in Data Analytics

About the Data Analytics course block

We live in a data-centered world, and the ability to make data-driven decisions and craft strategy informed by an effective analysis of data are key elements of successful leadership in any work environment. The Data Analytics course block  is a sequence designed to provide a reasonable point of entry for individuals to gain expertise in data analytics. Courses are scheduled at times to accommodate working adults, so you can improve your data literacy while working on your career. Courses are taught by experts and experienced practitioners, including members of the Penn faculty from the Penn Program on Opinion Research and Election Studies. You don’t need an extensive background in math, statistics, or programming to succeed in the data analytics course block. The only prerequisites are a familiarity with using a computer, basic math skills, and a willingness to learn.

Bachelor of Applied Arts and Sciences degree courses in the Data Analytics course block are offered on an accelerated (8-week) schedule. Courses in the block are largely asynchronous with some optional synchronous sessions to be scheduled by the instructors.

Although the courses can be taken sequentially to build your expertise in data analytics, you have the option to enroll in any or all of the courses within this course block without committing to the degree, enjoying the flexibility and expertise offered by Penn LPS Online to suit your schedule and interests. All Penn LPS Online courses offer academic credit.*

Please note: Students completing this course block while enrolled in the Bachelor of Applied Arts and Sciences (BAAS) degree are awarded a Certificate in Data Analytics upon completion of the degree. If you are enrolled in the BAAS program and don't complete the degree requirements to graduate, you are not eligible to receive this certificate.

*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.

The Data Analytics course block prepares you to:

  • Implement and interpret basic regression models
  • Understand advanced predictive modeling and machine learning
  • Implement and analyze surveys
  • Design experiments and A/B tests to test solutions and address problems
  • Develop skills in statistical programming and data analysis in R
  • Apply skills and knowledge to solve real-world problems

Meet the Faculty

John Lipinski

John Lipinski

Faculty Director for the Data Analytics Certificate


Basic courses

Advanced courses

Courses are subject to change.