Minor in Data Science

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).

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. 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 2006 Computational Probability
• DS 3001 (formerly 4001 Practice of Data Science): Foundations of Machine Learning 
• DS 3005 Mathematics for Data Science
• CS 4774 Machine Learning
• PSYC 5710 Machine Learning and Data Mining
• STAT 5630 Statistical Machine Learning
• APMA 3150 / STAT 3080: From Data to Knowledge (No longer meets the requirement for students who declare the minor during Summer 2023 or later.)

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 3636 Neural Network Models
• BME 4000: Machine Learning 
• CHE 4561: Data Science in Chemical Engineering 
• COMM 4260: Business Analytics 
• COMM 4351 - Marketing Analytics for Big Data
• COMM 4230: Info Technology in Finance 
• COMM 4522 Topics in Business Analytics

• COMM 4559 – New Course in Commerce

      Approved Topic: Business Analytics with Python   
      Approved Topic: Ethical Application of Artificial Intelligence

• CS 3710: Introduction to Cybersecurity 
• CS 4501 Human-Robot Interaction
• CS 4774: Machine Learning (No longer meets the requirement for students who declare the minor during Summer 2023 or later.)
• DS 5110 Big Data Systems
• ENGL 3500: Hacking for Humanists 
• EVSC 3020 GIS Methods
• EVSC 4080: Quantitative Methods in Environmental Sciences 
• EVSC 5040 Messy Data
• GSVS 4100 Evidence for Sustainability Policy
• PHS 3102: Introduction to Public Health Research: Population Data Analysis 
• STAT 4220 Applied Analytics for Business
• STAT 4630: Statistical Machine Learning 
• STAT 4800 Advanced Sports Analytics I (formerly STAT 4559 Sports Analytics)
• STAT 4996: Capstone
• Other courses may be approved by the program director.

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

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 3

Complete this minor declaration form.

Step 4 (Optional)

Meet with a data science advisor to discuss your plan to complete the minor. Advising takes place on Mondays when classes are in session during the fall and spring semesters from 10:00-11:30am via Zoom.

Step 5

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.

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 and am pursuing a major that includes the 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. 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. 

Meet with a data science advisor to discuss your plan to complete the minor. Advising takes place on Mondays when classes are in session during the fall and spring semesters from 10:00-11:30am 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.