Major Requirements
Degree Type: B.S.
Minimum Credits Required: 120
University Degree Requirements
For complete details on these and other university degree requirements, refer to the Degree and Graduation Requirements section in the University Catalog.
- Minimum of 120 semester credits (some programs may exceed this minimum).
- Complete the University General Education requirements.
- Minimum institutional GPA of 2.00 based on work taken at NDSU.
- Minimum of 30 credits in resident at NDSU.
- Minimum of 36 upper level credits (courses numbered 300 or higher).
- Students with transfer credit must meet the NDSU 30 credits in residence (#4). Of these 30 credits in residence, a minimum of 15 credits must be in courses numbered 300 or above, and 15 credits must be in the student's declared major curricula.
University General Education Requirements
A list of university approved general education courses along with the administrative policies governing the requirement and the categories is available here.
Course List Code | Title | Credits |
Total Credits | 39 |
Course List Code | Title | Credits |
| 3 |
| Computer Applications | |
| Business Software Applications | |
| Computer Science Problem Solving | |
| Introduction to UNIX | |
ENGL 321 | Writing in the Technical Professions | 3 |
or ENGL 324 | Writing in the Sciences |
BUSN 380 | Business Analytics: Business Problem Solving with Spreadsheets | 3 |
MATH 165 | Calculus I | 4 |
MATH 166 | Calculus II | 4 |
STAT 367 | Probability | 3 |
STAT 368 | Statistics | 3 |
STAT 412 | Statistics for Data Science using R | 3 |
STAT 460 | Applied Survey Sampling | 3 |
MIS 340 | Applied Business Intelligence | 3 |
MIS 479 | Business Data Mining and Predictive Analytics | 3 |
CSCI 312 | Survey of Programming Languages | 3 |
CSCI 222 | Discrete Mathematics | 3 |
CSCI 227 | Computing Fundamentals in Python I | 3 |
CSCI 228 | Computing Fundamentals in Python II | 3 |
CSCI 161 | Computer Science II | 4 |
CSCI 366 | Database Systems | 3 |
| 3 |
| Business Ethics | |
| Social Implications of Computers | |
| Ethics, Engineering, and Technology | |
| 12 |
Total Credits | 69 |
Track One: Artificial Intelligence
Course List Code | Title | Credits |
| 12 |
| Software Development with Frameworks | |
| Introduction to Data Science in Python | |
| Fundamentals of Data Engineering | |
| Machine Learning | |
| Introduction to Artificial Intelligence | |
| Artificial Intelligence, Ethics, and the Environment | |
| Cloud Computing | |
| Introduction to Data Mining (Introduction to Data Mining) | |
Total Credits | 12 |
Track Two: Statistical Data Analytics
Course List Code | Title | Credits |
STAT 462 | Introduction to Experimental Design | 3 |
STAT 463 | Nonparametric Statistics | 3 |
STAT 464 | Discrete Data Analysis | 3 |
STAT 470 | Statistical SAS Programming | 3 |
Total Credits | 12 |
Track Three: Business Analytics
Course List Code | Title | Credits |
MRKT 466 | Digital Marketing Analytics | 3 |
SCM 330 | Supply Chain Analysis and Analytics | 3 |
SCM 455 | Supply Chain Technology Enablers | 3 |
MIS 350 | Enterprise Systems | 3 |
Total Credits | 12 |
Track Four: Generalist
Course List Code | Title | Credits |
| 12 |
| Operations Research I | |
Total Credits | 12 |