Data Science
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. Indeed, there are few if any fields in which the tools of data science are not increasingly relied upon, and the demand for people with the right skills continues to grow. The Data Science B.S. program at Â鶹´«Ã½gives 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 for decision-making. Beginning with foundational mathematics, statistics, and computing, you will develop techniques in data mining, statistical and machine learning, predictive modeling, and data visualization. Industry partnerships with local employers provide opportunities to refine your expertise through project based learning experiences throughout the curriculum as well as in a senior practicum. These partnerships have also created pathways to permanent employment for our graduates.
Curricular Requirements
Credits | |
CAS CORE REQUIREMENTS (EXCLUDING MATHEMATICS) | 39-42 |
Credits | |
Program Required Courses | |
MAT 150 - Statistics for Life Sciences | 3 |
MAT 190 - Calculus I | 4 |
MAT 195 - Calculus II | 4 |
DSC 205 - Introduction to Data Analysis and Modeling | 3 |
MAT 212 - Applied Discrete Mathematics | 3 |
MAT 220 - Applied Linear Algebra | 3 |
MAT 225 - Computer Programing w/ MATLAB | 3 |
MAT 301 - Database Design and SQL | 3 |
MAT 315 - Applied Mathematics w/ Differential Equations | 3 |
MAT 321 - Applied Statistics I | 3 |
MAT 323 - Applied Statistics II | 3 |
MAT 3XX - Data Structures | 3 |
DSC 2XX - Data Visualization | 3 |
DSC 3XX - Programming II | 3 |
DSC 4XX - Data Mining | 3 |
DSC 4XX - Practicum | 3 |
DSC 4XX - Topics in Data Science | 3 |
DSC 4XX - Predicitive Analytics | 3 |
Program Minimum Required Total Credits | 56 |
Open Elective Courses (Needed to reach 120) | 27 |
Minimum Required Total Credits | 122-125 |
Learning Outcomes
Students successfully completing the B.S. in Data Science will:
- Combine mathematical and statistical models with computational techniques and technologies for prediction and decision making.
- Demonstrate an understanding of algorithmic complexity, scalability, and the limitations of techniques and technologies, and assess validity of results.
- Use current field specific technology 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.
Honors Program
We offer qualified students the option of graduating with Honors. This includes significant research, scholarship or creative activity under the direction of a faculty member. Interested students should consult with their major advisor.
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 Â鶹´«Ã½in 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 also.
Admissions
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.