The Data Science and Analytics minor provides students with a foundation in the methodology of data science coupled with disciplinary applications that students can select in accordance with their interests. The minor is open to all students and can be tailored to best complement any major field of study. The goal of the minor is for students to develop skills in the theory and application of quantitative methods used to conduct original research in their field. Details on the curriculum and requirements for the minor are available here. Note that courses are not necessarily taught every semester or every year.
Students interested in declaring the data science minor should carefully review the requirements. If you have any questions, please consult with your faculty advisor and DDDI’s Assistant Director for the DASA Minor, Joelle Gross. Students must meet with Joelle before declaring the minor. Remaining questions about the program or the approval process for declaring the minor can be addressed to Dr. Colin Twomey. Students who are expecting to graduate in May 2024 should contact us as soon as possible to make sure the requirements are met.
Proposing an Exception
Students may propose that a course not listed in the existing curriculum for the DASA minor be counted towards the requirements for the minor. To make an exception request, please contact Joelle Gross with the course that you would like to count. Please send the syllabus for the proposed exception, along with a rationale for the request (following the criteria below).
Exception for a Core Course
To substitute for a course in one of the three core topic areas (Introductory Data Science and Programming, Math and Statistics, or Applied Data Science), the course must cover substantially similar material as one of the approved courses. Your request should specify which of the approved courses is most similar to the proposed exception.
Exception for an Elective
An exception for an elective should meet one or more of the following criteria:
- A theoretical, computational, or applied treatment of data science methods. Topics that would meet this criterion include: optimization, linear algebra, and database tools for working with large datasets.
- Substantial analysis of empirical data. For example, a course in which students write a final research paper that involves original data analysis would count for this criterion, but a course in which students summarize existing data analysis would not.
- Students must have at least three courses that count only towards the DASA minor’s requirements. In other words, at most three of the six courses required for the DASA minor may overlap with the requirements for other majors or minors.
- At least one of the three electives in your course of study must have a substantial data analysis component. In general, every elective should be chosen to enhance practical and/or theoretical data science skills.
- Two courses that substantially overlap in material covered cannot both be counted towards the minor. E.g. only one of MATH 2400 and MATH 3120 would be counted, but both MATH 2400 and MATH 3130 (Computational Linear Algebra), or both MATH 2400 and MATH 3140 (Advanced Linear Algebra) could be counted.
- Only one study abroad course may be counted towards the minor.
- At least three of the six courses for the minor must be in the College. Note that one of these three may be from a study abroad course if it is counted in the College.
The minor consists of six courses, three of which are foundational and must fall into specific components (Introductory Data Science & Programming, Math & Statistics, Applied Data Science) and the remaining three are electives that must have a strong link to data science.
Introductory Data Science & Programming (1 c.u.)
|Foundations in Data Science for Comm.
|Criminal Justice Data Analytics
|Data Science for Studying Language and the Mind
|Introduction to Data Science
|Data Analytics and Statistical Computing
|Statistics for Biologists
|Computational Data Exploration
|Data Science for the Humanities
|Foundations of Data Science
|Introduction to Computational Physics
|Introduction to Python for Data Journalism
Math & Statistics (1 c.u.)
|Statistics for the Social Sciences I
|Statistics for Economists
|Introduction to Data-driven Modeling
|Biological Data Science I – Fundamentals of Biostatistics
|Data Analysis for the Natural Sciences I: Fundamentals
|Statistical Methods PSCI
|Introductory Business Statistics
Applied Data Science (1 c.u.)
|Biological Data Analysis
|Econometric Machine Learning Methods and Models
|Applied Data Science
|Introduction to Bayesian Data Analysis
|Modern Data Mining
|Machine Learning for the Social Sciences
|Data Science for Public Policy
|Applied Machine Learning
|Data Analysis for the Natural Sciences II: Machine Learning
|Big Data Analytics
|Tiny Machine Learning
|Artificial Intelligence Lab: Data, Systems, and Decisions
Electives (3 c.u)
|Introduction to Computational Biology & Biological Modeling
|Computational Text Analysis for Communication Research
|GIS: Mapping Places & Analyzing Spaces
|Database and Information Systems
|Big Data, Memory and the Human Brain
|Phonetics II: Data Science
|Computer Analysis and Modeling of Biological Signals and Systems
|Physical Models of Biological Systems
|Health of Populations
|GIS Applications in Social Science
|Introduction to Digital Anthropology
|Data Analysis for Marketing Decisions
|Survey Research & Methods
|Talking AI Computational and Communication Approaches
|Climate Change and Big Data
Data Science at Penn
Penn offers a number of pathways when it comes to integrating data science into your course of study. Which path is right for you will depend on your goals.
- Data Science and Analytics Minor (DASA; this page). The DASA minor is designed to complement any major field of study in the natural and social sciences. The path offered by this minor trains students to use data to answer applied research questions in their respective field.
- Survey Research & Data Analytics Minor (SRDA). The Survey Research & Data Analytics minor focuses on understanding public opinion and elections through the use of survey research and data analysis. The SRDA path offers students a deeper substantive focus on politics, elections, and public opinion.
- Digital Humanities Minor. This course of study is intended for students in the humanities rather than the natural and social sciences.
- SEAS Data Science Minor (DATS). The DATS minor introduces students to a wide range of mathematical and computational tools for data science with application areas ranging from information systems and finance to data mining.
- Wharton Statistics and Data Science Minor. Relative to the College Data Science & Analytics minor, this course of study emphasizes classical probability theory and statistics, along with their mathematical underpinnings.
- Annenberg Data and Network Science concentration. The focus of this concentration is on data science for understanding social networks and communication. It is only open to Communications Majors.
Assistant Director, Data Science and Analytics Minor
Dr. Colin Twomey
Interim Executive Director for DDDI
Faculty Advisor for students in the Social Sciences
Faculty Advisor for students in the Natural Sciences