DATA 1010: Introduction to Data Analytics

Data Analytics
Course in Data Analytics
Course Description:

In our digital world, data-driven decision-making is becoming more common and more expected. Effective leadership and communication, therefore, often hinges on the ability to acquire, manage, analyze, and display large, quantitative data sets. Even many entry-level jobs assume or require basic knowledge of data analytics. This online data analytics course introduces students to important concepts in data analytics across a wide range of applications using the programming language R. Students complete the course with a clear understanding of how to utilize quantitative data in real-time problem identification, decision-making, and problem-solving. No prerequisites in statistics or math are required.

Prior to the start of the term, students in DATA 1010 are required to complete a pre-course module that takes approximately 3-5 hours. During this time, students download and set up the software they will use for this class and ensure that it is properly configured for their machine. Students must complete this task approximately two weeks before the term begins (if more time is needed, students are encouraged to connect with their instructor or advisor). To ensure that students are successful with this pre-course model, there is supplementary support available from teaching assistants throughout the pre-course period. These support sessions will be announced on the Canvas course site, which students can access once they are registered for the course.

You have the option to enroll in this individual course without committing to the entire Certificate in Data Analytics, enjoying the flexibility and expertise offered by Penn LPS Online to suit your schedule and interests. Data Analytics courses are in high demand admit a limited number of students each term. Early registration is recommended. This course is offered in both fall and spring terms. To confirm whether registration is still open for a specific term before you enroll, please email lpsonline@sas.upenn.edu or call (215) 746-6903.

Course Credits:
1 course unit (c.u.)*
Term Format:
Accelerated 8-Week Term
2025 Term Offered:
Spring 1: Jan 15 – Mar 12, 2025
Spring 2: Mar 17 – May 09, 2025
Synchronous Session:
Weekly synchronous session required:
Synchronous Session:
Online seminars meet Thursdays from 6 - 7 p.m., ET
BAAS Foundational Requirement:
Quantitative Analysis - Statistics

*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.

Instructors

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

Stephen Pettigrew

  • Director of Data Sciences, Penn Program on Opinion Research and Election Studies

Stephen Pettigrew is the Director of Data Sciences of Penn Program on Opinion Research and Election Studies and the Deputy Executive Director of the Fox Leadership Program at the University of Pennsylvania. Prior to coming to Penn, Stephen received a PhD in political science and a master’s degree in… Read more

Nicky Bell

  • Director of Data Science, Clairity, Inc.

Nicky Bell is a data scientist and educator with more than a decade of experience managing data projects in academic and corporate settings. A graduate of the PhD program in political science at Penn, he currently leads statistical evaluation and data governance programs at Clairity, Inc., an AI-focused healthcare startup. Before that, he… Read more

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