Applied Data Analytics, Minor
The Minor in Applied Data Analytics allows students to choose among Information Systems, Statistics, and Marketing courses to learn about data management and analysis.
Program Requirements
| Code | Title | Credit Hours |
|---|---|---|
| Total Credit Hours | 18 | |
| Discipline Core Requirements | 6 Credits | |
| INFO 2410 | Database Fundamentals | 3 |
| INFO 3130 | Introduction to Applied Data Analytics | 3 |
| Elective Requirements | 12 Credits | |
| Complete 12 hours of the following: | 12 | |
| Database Systems and Warehousing (3) | ||
| Data Visualization (3) | ||
| Data Science and Big Data Analytics (3) | ||
| Marketing with Social Media (3) | ||
| Digital Marketing Analytics (3) | ||
| Sales Operations (3) | ||
| Design of Experiment (3) | ||
| Survey Sampling (3) | ||
| Multivariate Analysis WE (3) | ||
| Nonparametric Statistics (3) | ||
| Introduction to Data Analysis for Biologists (3) | ||
Other advisor-approved elective | ||
Graduation Requirements
1.Completion of a minimum of 18 semester credits.
2.Minimum grade of C- required in all courses.
3.Overall grade point average of 2.0 (C) or above.
4.Residency hours: minimum of 9 credit hours through course attendance at UVU.
Graduation Plan
This graduation plan is a sample plan and is intended to be a guide. Your specific plan may differ based on your Math and English placement and/or transfer credits applied. You are encouraged to meet with an advisor and set up an individualized graduation plan in Wolverine Track.
| First Year | ||
|---|---|---|
| Semester 1 | Credit Hours | |
| INFO 2410 | Database Fundamentals | 3 |
| INFO 3130 | Introduction to Applied Data Analytics | 3 |
| Credit Hours | 6 | |
| Semester 2 | ||
| Minor Elective | 3 | |
| Credit Hours | 3 | |
| Second Year | ||
| Semester 3 | ||
| Minor Elective | 3 | |
| Credit Hours | 3 | |
| Semester 4 | ||
| Minor Elective | 3 | |
| Credit Hours | 3 | |
| Third Year | ||
| Semester 5 | ||
| Minor Elective | 3 | |
| Credit Hours | 3 | |
| Total Credit Hours | 18 | |
Program Learning Outcomes
- Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
- Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program's discipline.
- Produce computer models, analyses, and visualizations that meet business needs.