The Minor in Data Science is jointly offered by the Department of Statistics and Department of Mathematics in the McCausland College of Arts and Sciences and the Department of Computer Science and Engineering in the Molinaroli College of Engineering and Computing. It corresponds to both the Data Science B.S. and Data Analytics B.S. and is designed for students in any discipline that uses large data sets, including the sciences, engineering, business, mathematics, and the social sciences.

Degree Requirements (18-19 Hours)

Prerequisites (3-4 hours)

Course List

Course	Title	Credits
MATH 122	Calculus for Business Administration and Social Sciences	3
or MATH 141	Calculus I
Total Credit Hours		3

Minor Requirements (18 or 19 Hours)

must be passed with a grade of C or higher

Course List

Course	Title	Credits
Minor Core Courses		12-13
CSCE 106	Scientific Applications Programming
or CSCE 145	Algorithmic Design I
STAT 509	Statistics for Engineers
or STAT 515	Statistical Methods I
or STAT 301	Statistical Methods for Data Analytics
CSCE/STAT 587	Big Data Analytics
or STAT 530	Applied Multivariate Statistics and Data Mining
CSCE 567	Visualization Tools
or STAT 542	Computing for Data Science
Minor Elective Courses		6
Some of these options may have additional prerequisites.
Select two courses from:
Any of CSCE 567, CSCE 587/STAT 587, STAT 530 or STAT 542 not taken as a minor core course.
CSCE 146	Algorithmic Design II
CSCE 520	Database System Design
CSCE 556	Analysis of Experimental Data in Python
CSCE 564	Computational Science
CSCE 569	Parallel Computing
CSCE 580	Artificial Intelligence
CSCE/STAT 582	Bayesian Networks and Decision Graphs
CSCE 585	Machine Learning Systems
CSCE 588/STAT 531	Advanced Machine Learning with Implementation
MATH 328	Mathematical Concepts for Data Analytics
MATH 344	Applied Linear Algebra
or MATH 544	Linear Algebra
MATH 374	Discrete Structures
or MATH 574	Discrete Mathematics I
MATH/STAT 511	Probability
MATH 524	Nonlinear Optimization
MATH 528	Mathematical Foundation of Data Science and Machine Learning
MATH 529	Introduction to Deep Neural Networks
MATH 572	Mathematical Foundation of Network Science
STAT 506	Introduction to Experimental Design
STAT/MATH 511	Probability
STAT 512	Mathematical Statistics
STAT 516	Statistical Methods II
STAT 517	Advanced Statistical Models
STAT 519	Sampling
STAT 531/CSCE 588	Advanced Machine Learning with Implementation
STAT 535	Introduction to Bayesian Data Analysis
STAT 540	Computing in Statistics
STAT 541	Advanced SAS Programming
STAT/CSCE 582	Bayesian Networks and Decision Graphs
STAT/BIOL 588	Genomic Data Science
Total Credit Hours		18-19

Note: The Data Science Minor is designed for students in any discipline that uses large data sets, including Biology, Business, Psychology, etc. Choosing the correct courses is more complicated for students majoring in Computer Engineering, Computer Science, Computer Information Systems, Mathematics, and Statistics.

Restrictions and Course Substitutions

The Data Science Minor may not be taken by a student completing the Data Science B.S. or Data Analytics B.S.. 

No course may be applied to both the Data Science Minor and the Carolina Core, a Major Requirement, or an additional minor.  In the event of a conflict, a Minor Elective Course may be substituted for a Minor Required Course in this minor.

All courses applied to the minor must have been passed with a grade of C or higher.

Administration of the Minor

Curricula and oversight decisions for the minor are approved by both the McCausland College of Arts and Sciences and the Molinaroli College of Engineering and Computing. The Data Analytics B.S. and Data Science B.S. Program Committees propose curricular changes and address advising decisions such as course substitutions.