The Minor in Data Science will expose students to the conceptual framework for the emerging field of data science, including four central areas of focus: analytics, systems (data engineering), design (communications), and value (ethics). These components combine to form the practice of data science. Through exposure to these critical domains of data science, students in the minor will receive the education needed to understand rapidly evolving data science concepts from theory to practice.
Earning a minor in data science will prepare you for careers or post-graduate work using data skills, providing a solid foundation for further exploration in the field. Join our community of undergraduate data science students!
Students who have declared the Data Science Minor should check Stellic for the academic requirements.
For students considering the Data Science Minor, here are the Data Science Minor requirements starting Fall 2026:
Minor students are required to take one course from each of the five categories listed below, totaling 15 credits; four courses (12credits) must be data science (DS) courses. DS 1001 Foundation of Data Science can be counted as one of the 4 required DS courses.
Foundational Programming Course (select one)
• DS 1002 - Programming for Data Science Credits: 3
• CS 1110 - Introduction to Programming Credits: 3
• CS 1111 - Introduction to Programming Credits: 3
• CS 1112 - Introduction to Programming Credits: 3
• CS 1113 - Introduction to Programming Credits: 3
• PHYS 1655 - Introduction to Python for Scientists and Engineers Credits: 3
• The Foundational Programming requirement may not be substituted with another course taken at a higher level or the CS 1110 place-out test. Students who are ineligible to enroll in a Foundational Programming course due to previous experience may take an additional course in another area to total 15 credits for the minor. Students should enroll in an approved minor course and email SDSMinor@virginia.edu to ensure the requirement is satisfied in SIS.
Analytics Course (select one)
• DS 3001 - Foundations of Machine Learning Credits: 3
• CS 4774 - Machine Learning Credits: 3
• STAT 5630 - Statistical Machine Learning Credits: 3
Systems Course (select one)
• DS 2002 - Data Science Systems Credits: 3
• CS 4750 - Database Systems Credits: 3
• COMM 3220 - Data Management for Decision Making Credits: 3 (for Commerce majors only)
• SYS 2202 - Data and Information Engineering Credits: 3 (Systems majors only)
Data Design & Value (select one)
• DS 2003 - Communicating with Data Credits: 3
• DS 2004 - Data Ethics Credits: 3
• SARC 5400 - Data Visualization Credits: 3
• COMM 4221 - Data Exploration and Visualization with R Credits: 3
• NUIP 2311 - Research, Ethics, Advocacy, and Leadership: Intro to Professional Practice Credits: 2
• NUIP 4311 - Research, Ethics, Advocacy, and Leadership Credits: 2
• STS 4600 - The Engineer, Ethics, and Professional Responsibility Credits: 3
Domain Elective (select one)
• DS 4002 - Data Science Project Credits: 3
• DS 4993 - Independent Study Credits: 3 to 4
• DS 4995 – Directed Study Credits: 3 to 4
• DS 5110 - Big Data Systems Credits: 3
• CHE 4452 - Data Science in Chemical Engineering Credits: 3
• COMM 4210 Managerial View of AI meets this requirement
• COMM 4211: Ethical Application of Artificial Intelligence
• COMM 4230 - Fintech: Information Technology in Finance Credits: 3
• COMM 4351 - Marketing Analytics for Big Data Credits: 3
• COMM 4522 - Topics in Business Analytics Credits: 3
Approved Topic: Business Analytics with Python
Approved topic: Foundations of Machine Learning and AI with Low-Code
Approved topic: Foundations of Machine Learning and AI w/ Python
• CS 3710 - Introduction to Cybersecurity Credits: 3
• CS 4501 - Special Topics in Computer Science Credits: 1 to 3
• EVSC 3020 - GIS Methods Credits: 4
• EVSC 4080 - Computational Methods for Environmental Analysis Credits: 3
• GSVS 4100 - Evidence for Sustainability Policy Credits: 3
• PHS 3102 - Introduction to Public Health Research: Population Data Analysis Credits: 3
• STAT 4220 - Applied Analytics for Business Credits: 3
• STAT 4630 - Statistical Machine Learning Credits: 3
• STAT 4800 - Advanced Sports Analytics I Credits: 3