Minor in Data Science

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 science. This minor prepares students for careers or postgraduate work that necessitates exposure to data science techniques. Emphasis on responsible data science is included as a core principle of the program.

ADMISSIONS

Current undergraduate UVA students from any school of enrollment who have declared their major in SIS may declare the minor in Data Science by submitting the minor declaration form.

Requirements for Minor in Data Science

Complete a minimum of 15 graded credits:

12 graded credits in core areas

3 graded credits of an upper-level elective course within a domain OR the data science project course, and

a minimum of 3 courses/9 credits must be data science courses (DS XXXX).

A student’s elective course and any other courses outside of those defined in The Record are selected in consultation with School of Data Science advisors and the Program Director.

Foundational Programming Course (select one course)

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 2110 - Software Development Methods Credits: 3
PHYS 1655 - Introduction to Python for Scientists and Engineers Credits: 3

Analytics Course (select one course)

DS 2006 - Computational Probability Credits: 3
DS 3001 - Foundations of Machine Learning Credits: 3
DS 3005 - Mathematics for Data Science Credits: 4
CS 4774 - Machine Learning Credits: 3
PSYC - 5710 Machine Learning and Data Mining Credits: 3
STAT 5630 - Statistical Machine Learning Credits: 3

Systems Course (select one course)

DS 2002 - Data Science Systems Credits: 3
CS 4750 - Database Systems Credits: 3
COMM 3220 - Database Management Systems and Business Intelligence Credits: 3 (for Commerce majors only)
SYS 2202 - Data and Information Engineering Credits: 3 (Systems majors only)

Data Design & Value Course (select one course)

DS 2003 - Communicating with Data Credits: 3
DS 2004 - Data Ethics 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
PLAN 3813 - Community-Engaged Methods Credits: 3
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.

DS 4002 - Data Science Project Course Credits: 3
DS 5110 - Big Data Systems Credits: 3
BME 3636 - Neural Network Models of Cognition and Brain Computation Credits: 3
CHE 4561 - Special Topics in Chemical Engineering Credits: 1 to 3
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
COMM 4559 - New Course in Commerce Credits: 1 to 4
Approved Topic: Business Analytics with Python
CS 3710 - Introduction to Cybersecurity Credits: 3
CS 4501 - Special Topics in Computer Science Credits: 1 to 3
ENGL 3500 - Studies in English Literature Credits: 3
Approved Topic: Hacking for Humanists
EVSC 3020 - GIS Methods Credits: 4
EVSC 5040 - Messy Data Credits: 3
EVSC 4080 - Quantitative Methods in Environmental Sciences 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 4559 - New Course in Statistics Credits: 1 to 4
Approved Topic: Topics in Sports Analytics
STAT 4630 - Statistical Machine Learning Credits: 3
STAT 4800 - Advanced Sports Analytics I 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. The Analytics requirement of the minor must be completed before enrollment in this course.

Transfer Credit

Students may transfer up to one course, whether it be post- or pre-matriculation.

Students under suspension may not apply transfer credits from other institutions toward the minor.

Completion

The completion of the Data Science minor requires a minimum of 15 credits. 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, students’ schools of enrollment may restrict the double-counting of courses, which supersedes this minor’s policies. Students should consult with their School of Enrollment advisors and Registrar for policies on double-counting credits. A transferred course will count as a double-counted course.