Degree
Bachelor of Science in Data ScienceContact
Amy Deveau, Ph.D.
Academic Director, School of Mathematical and Physical Sciences
adeveau@une.edu
Eva Rose Balog, Ph.D.
Assistant Academic Director, School of Mathematical and Physical Sciences
ebalog@une.edu
Mission
The Data Science Bachelor of Science degree program inspires students to become innovators who make impactful contributions through data analysis, modeling, computation, and simulation. The program fosters flexible and creative approaches for problem solving and the ability to gain insights about complex relationships and interdependencies, and to describe and communicate these insights for prediction and decision making.
Major Description
In recent years the explosion of data in a wide range of fields has created a wealth of opportunities for data science professionals, and the demand for people with the right skills continues to grow. The Data Science B.S. program at SWAGÊÓƵ gives you the opportunity to apply your passion for mathematical modeling and computing to problems involving the analysis of data and the design of models for extracting information, making predictions, and decision-making.
Beginning with foundational mathematics, statistics, and computing, you will develop techniques in visualization, machine learning, and data mining.
Industry partnerships with local employers provide opportunities to apply these techniques and refine your expertise through project-based learning experiences throughout the curriculum as well as in a senior practicum.
Curricular Requirements
| CAS Core Requirements | Credits |
|---|---|
| Total | 42–46 |
| Program Required Courses | Credits |
|---|---|
| DSC 110 – Survey of Software Tools | 1 |
| DSC 130 – Exploring Data | 3 |
| DSC 225 – Programming I or MAT 225 – Computer Programming with MATLAB | 3 |
| DSC 260 – Data Visualization | 3 |
| DSC 301 – Introduction to Database Design/SQL | 3 |
| DSC 344 – Machine Learning | 3 |
| DSC 480 – Data Science Practicum | 3 |
| DSC 410 – Data Mining or DSC 420 – Predictive Modeling or DSC 490 – Topics in Data Science | 3 |
| MAT 120 – Statistics or MAT 150 – Statistics for Life Sciences | Credits included in Core Requirements |
| MAT 190 – Calculus I | 4 |
| MAT 220 – Linear Algebra | 3 |
| Total | 29 |
| Choose Four (4) Elective Courses | Credits |
|---|---|
| DSC 205 – Introduction to Data Analysis and Modeling | 3 |
| DSC 270 – Data Structures and Algorithms | 3 |
| DSC 325 – Programming II | 3 |
| GIS 364 – Spatial Data Analysis | 3 |
| MAT 195 – Calculus II | 3 |
| MAT 212 – Discrete Mathematics | 3 |
| MAT 323 – Applied Regression Analysis | 3 |
| MAT 340 – Graph Theory with Applications | 3 |
| MAT 405 – Introduction to Numerical Analysis | 3 |
| Total | 12 |
| Minimum Program Credits | 41 |
|---|---|
| Open elective credits (as needed to reach 120 credits) | Variable |
| Minimum Required Total Credits | 120 |
|---|
Learning Outcomes
Students successfully completing the B.S. in Data Science will:
- Develop, test, and deploy mathematical and statistical models for data analysis, prediction, and decision making
- Use current field-standard digital tools for data management, manipulation, organization, analysis, and visualization
- Effectively communicate quantitative information to technical and non-technical audiences orally, in writing, and through visual formats
Minors
A student with a major in another program may minor in Data Science with the approval of the academic director. A minimum of 18 hours of approved course credit is required.
Students wishing to declare a Data Science minor should complete a course plan in consultation with a Mathematical Sciences faculty member.
Students may earn a Minor in Data Science by completing 18-19 credits in the following:
| Required Courses | Credits |
|---|---|
| DSC 130 – Exploring Data | 3 |
| DSC 225 – Programming I or MAT 225 – Computer Programming with MATLAB | 3 |
| DSC 260 – Data Visualization | 3 |
| DSC 344 – Machine Learning | 3 |
| MAT 120 – Statistics or MAT 150 – Statistics for Life Sciences | 3 |
| Elective Credits* | 3–4 |
*Select at least one course from among DSC 205, DSC 301, DSC 410, DSC 420, DSC 490, and GIS 364.
Honors Program
At this time, Data Science does not offer Honors Program.
Transfer Credit
Courses previously completed at another accredited college can be transferred to this degree program beginning in Fall 2020. Transferred mathematics courses must be reasonably close in scope and content to the mathematics courses offered at SWAGÊÓƵ in order to count as exact equivalents. Otherwise, they will transfer as general electives.
All Science/Math courses previously completed must be no older than five years.
See Undergraduate Admissions for more information.
Admissions
See Undergraduate Admissions for more information.
Financial Information
Tuition and Fees
Tuition and fees for subsequent years may vary. Other expenses include books and housing. For more information regarding tuition and fees, please consult the Financial Information section of this catalog.
Notice and Responsibilities Regarding this Catalog
This Catalog documents the academic programs, policies, and activities of the SWAGÊÓƵ for the 2023–2024 academic year. The information contained herein is accurate as of the date of publication April 28, 2023.
The SWAGÊÓƵ reserves the right in its sole judgment to make changes of any nature in its programs, calendar, or academic schedule whenever it is deemed necessary or desirable, including changes in course content, the rescheduling of classes with or without extending the academic term, canceling of scheduled classes or other academic activities, in any such case giving such notice thereof as is reasonably practicable under the circumstances.
While each student may work closely with an academic advisor, he or she must retain individual responsibility for meeting requirements in this catalog and for being aware of any changes in provisions or requirements.