Data Science, B.S.

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Minimum number of credits required to graduate: 124

Minimum cumulative GPA required to graduate: 2.0

Minimum number of credits to complete the major: 60

School: School of Engineering and Computational Sciences

Department: Computer and Data Sciences

Learn more about the program

Data scientists use mathematics, statistics, and computer coding to transform raw data into meaningful information for decision making. Our majors develop competitive skills by using current industry software such as R, Python, and Tableau to analyze data sets drawn from application areas including transportation, business, health care, demographics, and sports. Our curriculum emphasizes teamwork, communication, and practical experience from the introductory courses through the internship and practicum. Students develop skills in data visualization, machine learning, data mining, and predictive analytics. The B.S. in Data Science provides a foundation in data science that produces graduates who are competitive within the thriving data science job market.

Overarching goals of the B.S. in Data Science program are to offer students more flexibility in their degree choices in the STEM fields, increase their career options, and provide one of the few B.S. in Data Science programs offered in New England within the current high-demand market for entry-level data scientists. A Data Science minor is also offered.

Major Requirements

The major consists of eight core courses: three required electives and four additional courses.

Core Courses

Complete the following required courses:

DSE 1001 - Foundations of Data Science I Credits: 4
DSE 1002 - Foundations of Data Science II Credits: 4
DSE 2001 - Creating Information Graphics Credits: 4
DSE 2010 - Machine Learning in Data Science Credits: 4
DSE 3001 - Data Mining and Predictive Analytics I Credits: 4
DSE 3002 - Data Mining and Predictive Analytics II Credits: 4
DSE 3800 - Special Topics in Data Science and Applied Statistics Credits: 4
DSE 4900 - Data Science Practicum Credits: 4

Major Electives

Choose three courses from the following:

CEN 3071 - Introduction to GIS Credits: 4
CHM 4430 - Introduction to Chemometrics Credits: 4
CSC 2820 - Data Structures Credits: 4
CSC 3810 - Databases Credits: 4
DSE 4620 - Advanced Sports Analytics Credits:
DSE 4800 - Directed Study in Data Science Credits: Variable
MTH 3335 - Linear Algebra Credits: 4

Additional Required Courses

Choose four courses from the following:

MTH 1314 - Discrete Mathematics Credits: 4
If choosing a Statistics course, choose one course from the following five courses:
PSY 2110 - Statistical Methods in Psychology Credits: 4
MTH 1110 - Basic Statistics with Fantasy Football Credits: 4
MTH 1111 - Basic Statistics Credits: 4
MTH 1505 - Applied Statistics and Probability for Engineers Credits: 4
MTH 2527 - Probability and Statistics I Credits: 4
If choosing a Computer Science course, choose one course from the following two courses:
CSC 1611 - Problem Solving with Python Credits: 4
CSC 2710 - Analysis of Algorithms Credits: 4
If choosing a calculus course, choose one course from the following two courses:
MTH 1115 - Calculus and Quantitative Methods for Business Credits: 4
MTH 1217 - Calculus I Credits: 4

Experiential Learning Component

All students are required to register at least one experience that is categorized by the department as experiential learning. Possible ways to fulfill this requirement include external or internal internships, research experiences, or semester projects. Students must seek approval by the department and register their experience with the O’Brien Center for Career Development.