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 post­graduate work using data skills, providing a solid foundation for further exploration in the field. Join our community of undergraduate data science students!

Prerequisite Courses

To qualify for the minor, students must take at least one of the following courses and earn a grade of C- or better:

  • APMA 3100 (Probability)
  • APMA 3110 (Applied Statistics and Probability)
  • APMA 3120 (Statistics)
  • PSYC 2005 (Research Methods and Data Analysis I)
  • PSYCH 2006 (Research Methods and Data Analysis II)
  • SOC 3120 (Sociology Research Workshop)
  • STAT 1000 (An Introduction to Statistics)
  • STAT 1100 (Chance: An Introduction to Statistics)
  • STAT 1120 (Introduction to Statistics)
  • STAT 1200 (Introduction to Statistics)
  • STAT 2120 (Introduction to Statistical Analysis)
  • STAT 1601 (Introduction to Data Science with R)
  • STAT 1602 (Introduction to Data Science with Python)
  • STAT 2020 (Statistics for Biologists)
  • Other courses may be considered upon request.

Minor Requirements

After satisfying the prerequisite requirement, minor students are required to take one course from each of the five categories listed below, totaling 15 credits; three courses (9 credits) must be data science (DS) courses. Students who declared the minor prior to Fall 2022 must complete two DS courses (6 credits).

Students in all schools EXCEPT the College of Arts and Sciences may double-count up to 2 courses (6 credits) between this minor and another program (major or minor). The College of Arts and Sciences does not permit double-counting courses towards majors and minors. Consult with your school of enrollment advisor and registrar for policies on double-counting credits toward other programs.

Foundational Programming Course (select one)

  • DS 1002 (formerly 2001): Programming for Data Science
  • CS 1110: Introduction to Programming
  • CS 1111: Introduction to Programming
  • CS 1112: Introduction to Programming
  • CS 2110: Software Development Methods
  • PHYS 1655: Introduction to Python for Scientists and Engineers

Analytics Course (select one) 

  • DS 3001 (formerly 4001 Practice of Data Science): Foundations of Machine Learning 
  • APMA 3150 / STAT 3080: From Data to Knowledge

Systems Course (select one)

  • DS 2002 (formerly 3002): Data Science Systems 
  • CS 4750: Database Systems (for CS majors)
  • COMM 3220: Database Management Systems and Business (for Commerce majors)
  • SYS 2202: Data and Information Engineering (for Systems Engineering majors)

Data Design or Value Course (select one)

Recommended Courses:

  • DS 2003 (formerly 3003): Communicating with Data
  • DS 2004: Data Ethics
  • SARC 5400: Data Visualization
  • APMA 2500 / STS 2500: Ethical Analytics 

The below courses are also options:

  • COMM 3810: Business Ethics
  • COMM 4559 Data Exploration and Visualization with R
  • LPPP 4210: Integrating Ethics in Public Policy
  • NASC 4200: Leadership and Ethics
  • NUIP 3311: Research, Ethics, Advocacy, and Leadership: Quality, Safety, and EBP
  • PLAN 3813-001: Methods of Community Research and Engagement, School of Architecture
  • LPPS 5360: Imagining Equitable Policy
  • STS 4600: The Engineer, Ethics, and Professional Responsibility
  • NUIP 4311: Research, Ethics, Advocacy, and Leadership
  • Other courses may be considered upon request.

Applied Data Science Course (select one)

  • DS 4002 Data Science Project Course - Students work in groups to complete several projects throughout the semester using different types of data (tabular, images, text, time, etc.)
  • Students can also select one of the following data science applied electives:
  • BME 4000: Machine Learning 
  • CHE 4561: Data Science in Chemical Engineering 
  • COMM 4260: Business Analytics 
  • COMM 4559: Business Analytics with Python 
  • COMM 4230: Info Technology in Finance 
  • CS 3710: Introduction to Cybersecurity 
  • CS 4774: Machine Learning 
  • ENGL 3500: Hacking for Humanists 
  • EVSC 4080: Quantitative Methods in Environmental Sciences 
  • PHS 3102: Introduction to Public Health Research: Population Data Analysis 
  • STAT 4800 Advanced Sports Analytics I (formerly STAT 4559 Sports Analytics)
  • STAT 4630: Statistical Machine Learning 
  • STAT 4996: Capstone
  • Other courses may be approved by the program director.

Declaring the Minor

The Minor in Data Science is open to students from all backgrounds, majors, and schools of enrollment. There is no application, and entry to the minor is not competitive. 

Step 1

Declare a major within your current school of enrollment. Your major must be reflected in SIS for the minor declaration to be processed. 

Step 2

Complete one of the prerequisite courses with a grade of C- or better.

Step 3

Review the minor requirements. Map out courses you have already taken toward the minor and your plan to complete any outstanding requirements, paying special attention to your school’s policy of double-counting courses and the requirement of three DS courses.

Step 4

Complete this minor declaration form

Step 5

Meet with a data science advisor to discuss your plan to complete the minor. Advising takes place on Fridays when classes are in session during the fall and spring semesters from 9:30-11:00am via Zoom.

Step 6

Once the minor declaration form is processed by both the School of Data Science and your school of enrollment, you will see the minor reflected in SIS and be able to enroll in DS courses.

Frequently Asked Questions

What’s the deal with double-counting?

We understand students may be completing majors and minors with overlapping coursework throughout the University, making the data science minor a winning complement to many degree programs. 

Data science courses count toward the graduation hours in any school of enrollment. The School of Data Science allows you to count up to two courses toward another major or minor. That said, your school of enrollment may restrict the double-counting of courses, which supersedes this minor’s policies. Contact your major advisor or school registrar to double-check their policies.

I’m in the College of Arts and Sciences pursuing a major that includes one or more requirements for the minor. Can I count these major requirements toward the data science minor? 

The College of Arts and Sciences Academic Rules state that “credits applied toward a major may not be applied toward a minor." Consult the Undergraduate Record for more information on academic rules.  

I’m not in the College of Arts and Sciences. Is my prerequisite course included in the two classes that I can double-count? 

No, you can double-count two courses in addition to the prerequisite. 

I’m in the College of Arts and Sciences and completed the prerequisite via test credit or for another major or minor. Do I need to take another course to satisfy the prerequisite course?

No, you will not need to take another course to meet the prerequisite, since it does not count toward the 15-credit minor requirement.

I’m not in the College of Arts and Sciences and am pursuing a major that includes the prerequisite, programming, and systems requirement for the minor. Can I count these major requirements toward the data science minor?

Yes, but the remainder of the minor courses must be data science courses (DS XXXX). 

Can I enroll in data science courses without being in the minor?

No. All DS courses that count toward the minor require students to have the minor declared in SIS. 

When can I declare the minor in data science?

You can declare the minor when your declared a major is reflected in SIS and when the prerequisite course has been completed or is in progress. Minor declaration forms will not be processed without a completed or in-progress prerequisite course or a major on record in SIS. 

Is there a specific order that minor courses must be taken? 

Students should take the programming requirement first, followed by systems and design, then analytics. The applied data science course is meant to be the culmination of your minor coursework and should be saved for the final course of the minor.

How do I get a course approved for one of the domain requirements or the applied data science course? 

Courses outside of those listed on the website may be reviewed on a case-by-case basis by Program Director Brian Wright. To request approval, send Professor Wright the syllabus (not just the course description) prior to enrolling in the class. 

For More Information

Meet with a data science advisor to discuss your plan to complete the minor. Advising takes place on Fridays when classes are in session during the fall and spring semesters from 9:30-11:00am via Zoom.

For questions about enrolling in courses toward the minor, declaring the minor, double-counting classes, or anything SIS-related, contact sdsminor@virginia.edu

For questions about if the minor is right for you, how the minor fits into your personal and professional goals, which classes would be best for your learning goals, and the field of data science, reach out to Program Director Brian Wright at brianwright@virginia.edu to set up an advising appointment.