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The purpose of the Bachelor of Arts in Data Science program is to train and produce an interdisciplinary data science work force to fill the growing need for this skill set across the state, region, and country. The target audience for this program includes students with high quantitative reasoning skills that have interest in mathematics and computer science, and also have the desire to develop innovative techniques to solve data-driven problems in a variety of disciplines. Students majoring in data science will interact with faculty from the Departments of Mathematics and Computer Science and Quantitative Reasoning, as well as choose a minor to support their data-sector interests. Throughout the major, students will engage with real-world problems and build a portfolio of data projects that will ready them for graduate study or an entry-level position in data analytics.
Many schools offer data science masters degrees or a bachelor’s degree that doesn’t require the choice of a concentration/minor. However, domain knowledge is a critical component of the data scientist’s toolbox. Our data science program is a Bachelor of Arts, which will require students to choose a minor. The minor will allow deeper exploration into a domain that aligns with the data science degree. Additionally, the program’s capstone experience will require students to work on a problem proposed by an industry, providing crucial experience to enter the workforce upon graduation successfully.
Capstone projects, undergraduate research (data science, statistics, machine learning),
internships, tutoring for Academic Success Center, tutoring for Mathematics Tutorial
Center, helping with summer camps and mathematical outreach programs for K-12 students.
Bachelor of Arts in Data Science
General Education | Semester Hours | ||||||
ACAD 101 | Principles of the Learning Academy | 1 | |||||
Shared Skills and Proficiencies | |||||||
Writing and Critical Thinking |
|||||||
WRIT 101 |
Composition |
3 |
|||||
HMXP 102 |
Human Experience |
3 |
|||||
CRTW 207 |
Critical Reading, Thinking & Writing |
3 |
|||||
Oral Communication |
Met in major with DSCI 402 (pending approval) |
0 |
|||||
Technology |
Met in major with CSCI 207/327 |
0 |
|||||
Intensive Writing |
Met in major with CSCI 327 |
0 | |||||
Constitution Requirement |
See approved list; may be met with another requirement |
0-3 | |||||
Physical Activity |
See approved list |
1 | |||||
Thinking Critically Across Disciplines | |||||||
Global Perspectives |
See approved list |
3 |
|||||
Historical Perspectives |
See approved list |
3 |
|||||
Introducing Students to Broad Disciplinary Perspectives | |||||||
Social Science |
see approved list; must include 2 designators |
6 |
|||||
Humanities and Arts |
see approved list; must include 2 designators |
6 |
|||||
Quantitative Skills and Natural Science |
(3 courses) |
3-4 |
|||||
Quantitative Skill |
Met in major with MATH 201 and MATH 202 |
0 |
|||||
Natural Science |
See approved list; must include one lab science |
3-4 |
|||||
Requirements in the Major | |||||||
MAED 200 |
Intro to Mathematica |
1 |
|||||
MATH 201,* 202,* |
Calculus I,II |
8 |
|||||
MATH 300 |
Linear Algebra |
3 |
|||||
MATH 341 |
Statistical Methods |
3 |
|||||
MATH 514 |
Regression Modeling |
3 |
|||||
CSCI 207*, 208* |
Intro to Comp Sci I & II |
8 |
|||||
CSCI 210 |
Programming Tools |
1 |
|||||
CSCI 271 |
|
4 |
|||||
CSCI 327 |
|
3 |
|||||
CSCI 355 |
|
3 |
|||||
DSCI 101 |
Data Science Seminar |
1 |
|||||
DSCI 201 |
Intorduction to Data Science |
3 |
|||||
DSCI 401 |
Data Mining |
3 |
|||||
DSCI 402 |
Data Science Capstone |
3 |
|||||
DSCI elective above 299 |
3 |
||||||
Minor | 15-24 | ||||||
Foreign Language Requirement | 3-8 | ||||||
General Electives |
2-20 |
||||||
Total |
120 |
^ This requirement may be met by a satisfactory score on a recognized examination or by passing any foreign language course numbered 102 or any course with 102 as a prerequisite.
*C- or better required.
Not more than 36 hours in any one subject designator may be applied toward the major
for a BA degree.
For additional degree requirements, please visit the Degree Requirements page.
***NEED TO UPDATE WITH DATA SCIENCE GRAPHIC****
Data scientist, data analyst, graduate study (masters or PhD program), operations
researcher, financial analyst, software engineer, statistician, actuary, risk analyst.