Program: Minor in Data Science - University of Virginia

Apr 13, 2025

Undergraduate Record 2022-2023

Return to School of Data Science: Courses & Programs

The minor in Data Science introduces students to the conceptual framework of data science. The pillars of that framework include analytical, systems, design and value components that uniquely combine to form the field of data sciences. This minor prepares students for careers or postgraduate work that necessitate exposure to data science techniques. Emphasis on responsible data science is included as a core principle of the program.

Data science is new and powerful in many ways but also builds on a foundation provided by computational and quantitatively oriented fields. Students in the minor receive the education needed to appreciate these new developments in the context of their theoretical heritage and practical application.

The minor was developed to leverage the established structure of the university in order to meet the requirements of what is an intrinsically interdisciplinary, dynamic, and externally engaged field. The traditional structure of higher education requires such enhancement—the feasibility of which has been established by the MSDS—in order to remain relevant to its students and to serve the Commonwealth and beyond.

Prerequisites

Students must have completed one of the courses below, with a minimum grade of C-.

Other courses may be proposed and are subject to approval by the Program Director.

APMA 3100 - Probability Credits: 3
APMA 3110 - Applied Statistics and Probability Credits: 3
APMA 3120 - Statistics Credits: 3
PSYC 2005 - Research Methods and Data Analysis I Credits: 3
PSYC 3006 - Research Methods and Data Analysis II Credits: 4
SOC 3120 - Sociology Research Workshop Credits: 4
STAT 1100 - Chance: An Introduction to Statistics Credits: 3
STAT 1120 - Introduction to Statistics Credits: 3
STAT 1601 - Introduction to Data Science with R Credits: 3
STAT 1602 - Introduction to Data Science with Python Credits: 3
STAT 2020 - Statistics for Biologists Credits: 4
STAT 2120 - Introduction to Statistical Analysis Credits: 4

Requirements for Minor in Data Science

The undergraduate minor in Data Science consists of four required courses and one elective course (or Data Science project course).

In completing the minor in data science, students are required to take at least three School of Data Science (DS) courses.

15 credit hours (not including the prerequisite course).

Data Design & Value Course (Select one course or suggest another course with Program Director approval)

DS 2003 - Communicating with Data Credits: 3
SARC 5400: Data Visualization - Credits 3
STS 2500 - Science and Technology in Social and Global Context Credits: 3
Approved Topic: Ethical Analysis
The following courses are also options:
COMM 3810 - Business Ethics Credits: 3
COMM 4559 - New Course in Commerce Credits: 1 to 4
Approved Topic: Data Exploration and Visualization with R
LPPP 4210 - Integrating Ethics in Public Policy Credits: 3
LPPS 5360 - Imagining Equitable Policy - Credits: 3
NASC 4200 - Leadership and Ethics Credits: 3
NUIP 3311 - Research, Ethics, Advocacy, and Leadership: Quality, Safety, and EBP Credits: 3
NUIP 4311 - Research, Ethics, Advocacy, and Leadership Credits: 2
STS 4600 - The Engineer, Ethics, and Professional Responsibility Credits: 3

Domain Elective (Select one course) Or Final Project as outlined below

Students can select a data-driven course from a domain area of interest with approval by the Program Director.

BME 4000 - Machine Learning
CHE 4561 - Special Topics in Chemical Engineering Credits: 1 to 3
COMM 4351 - Marketing Analytics for Big Data Credits: 3
COMM 4559 - New Course in Commerce Credits: 1 to 4
Approved Topic: Business Analytics with Python
COMM 4230 - Fintech: Information Technology in Finance Credits: 3
CS 3710 - Introduction to Cybersecurity Credits: 3
CS 4774 - Machine Learning Credits: 3
ENGL 3500 - Studies in English Literature Credits: 3
Approved Topic: Hacking for Humanists
EVSC 4080 - Quantitative Methods in Environmental Sciences Credits: 3
PHS 3102 - Introduction to Public Health Research: Population Data Analysis Credits: 3
STAT 4559 - New Course in Statistics Credits: 1 to 4
Approved Topic: Topics in Sports Analytics
STAT 4630 - Statistical Machine Learning Credits: 3
STAT 4996 - Capstone Credits: 3
Final Project

DS 4002 Final Project (DS course) - Students will be placed in groups and work through a series of data science projects throughout the semester. There will be a special focus on the ethics of the project to ensure full alignment with the School of Data Science defined model of data science. All other requirements of the minor must be completed before enrollment (via instructor permission) into this course.

Completion

The completion of the Data Science minor requires a minimum of 15 credits. A student may double-count no more than two courses between this minor and another program (major/minor); students should consult with their School of Enrollment advisors and Registrar for policies on double-counting credits.

Students may transfer up to one course, whether it be post or pre-matriculation. This limit is also included in the double-counting two course limit. For example, in the absence of a double-counting limit from the School of Enrollment, a student may transfer one course, and double-count a second course, thus meeting the two-course limit.

Minor in Data Science

Prerequisites

Requirements for Minor in Data Science

Foundational Programming Course (Select one course)

Analytics Course (Select one course)

Systems Course (Select one course)

Data Design & Value Course (Select one course or suggest another course with Program Director approval)

Domain Elective (Select one course) Or Final Project as outlined below

Completion