Data Science, B.S.
Contact
Ryan Hedstrom
Assistant Academic Director, School of Mathematics and Data Science
rhedstrom@une.edu
Mission
The Bachelor of Science with a major in Data Science 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 B.S. with a major in Data Science program at UNE gives students the opportunity to apply their 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, students will develop techniques in visualization, machine learning, and data mining.
Industry partnerships with local employers provide opportunities for students to apply these techniques and refine their expertise through project-based learning experiences throughout the curriculum as well as in a senior practicum.
Transfer Credit
See Undergraduate Admissions for more information.
Admissions
See Undergraduate Admissions for more information.
Financial Information
Tuition and fees for subsequent years may vary. Other expenses include books and housing. For more tuition and fee information, please consult this catalog’s Financial Information section.
Curricular Requirements
| Code | Title | Hours |
|---|---|---|
| Nor'easter Core Requirements | ||
| Nor'easter Core Requirements | 40 | |
| Program Required Courses | ||
| DSC 110 | Survey of Software Tools | 1 |
| DSC 130 | Exploring Data | 3 |
| DSC 225 | Programming 1 | 3 |
| DSC 260 | Data Visualization | 3 |
| DSC 301 | Intro to Database Design/SQL | 3 |
| DSC 344 | Machine Learning | 3 |
| DSC 360 | Deep Learning | 3 |
| DSC 480 | Data Science Practicum | 3 |
| MAT 120 | Statistics | 3 |
| or MAT 150 | Statistics for Life Sciences | |
| MAT 190 | Calculus I | 4 |
| MAT 220 | Linear Algebra | 3 |
| One 400-level course with the DSC prefix | 3 | |
| Select Four of the Following: | 12 | |
| Introduction to Data Analysis and Modeling | ||
DSC 270 | (Data Structures and Algorithms) | |
| Programming II | ||
| Deep Learning | ||
| Calculus II | ||
| Discrete Mathematics | ||
| Graph Theory w/Applications | ||
| Intro to Numerical Analysis | ||
| Probability | ||
| Statistical Methods I: Linear Models | ||
Any 300-level course with the STS prefix | ||
| Open Elective Courses (Students complete open elective credits as necessary to meet the University’s 120-credit minimum for graduation. The total number of elective credits required will depend on the student’s completed program, core, and other degree requirements.) | 36 | |
| Total Hours | 123 | |
Please note: While some courses can fulfill both core and program requirements, the credits earned do not count twice towards the minimum total required credits for the degree.
Learning Outcomes
Students successfully completing the B.S. with a major 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