Data Science - Minor

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College of Science

Department of Computer Science

Department of Mathematics and Statistics

Data Science is an interdisciplinary field that includes the management, analysis, and visualization of data to make the best possible evidence-based decisions, and draws primarily from the fields of Statistics and Computer Science. Scientists and engineers in today’s workforce have vast amounts of data available to them, but too often they do not have sufficient Data Science expertise to make full use of the data. With so much of today’s STEM innovation being data-driven, expertise in collecting, analyzing, and operationalizing data is critical to industry success. The primary audience for this minor is students in STEM majors, who will enter the workforce with core science skills, and this Data Science minor will strengthen their ability to create Data Science tools and utilize them to add value in the workforce.

All grades for MATH, STAT, and CS courses applied toward the Data Science minor must be C- or better.

Mathematics Core

Students will take the following courses:

MATH 1210 - Calculus I (QL) 4 credit(s)
MATH 2270 - Linear Algebra (QI) 3 credit(s)

Computer Science Core

Students will take the following courses:

CS 1400 - Introduction to Computer Science–CS 1 4 credit(s)
CS 1410 - Introduction to Computer Science–CS 2 (QI) 3 credit(s)
CS 2420 - Algorithms and Data Structures–CS 3 (QI) 3 credit(s)

Statistics Core

Students will take the following courses:

STAT 2000 - Statistical Methods (QI) 4 credit(s) or
STAT 3000 - Statistics for Scientists (QI) 3 credit(s) or
STAT 3080 - Data Science for Scientists 3 credit(s)
STAT 5100 - Modern Regression Methods (CI/QI) 3 credit(s)

Data Science Electives

Students will take 9 credits from the following list:

CS 5060 - Decision Making: Algorithms Under Uncertainty 3 credit(s)
CS 5080 - Data Mining 3 credit(s)
CS 5665 - Machine Learning for Data Science 3 credit(s)
CS 5820 - Interactive Information Visualization for Data Science 3 credit(s)
CS 5830 - Data Science in Practice 3 credit(s)
STAT 5050 - Introduction to R 1 credit(s)
STAT 5080 - Data Technologies 2 credit(s)
STAT 5550 - Statistical Visualization I 2 credit(s)
STAT 5555 - Advanced R Programming for Data Science 3 credit(s) or
STAT 6555 - Advanced R Programming for Data Science 3 credit(s)
STAT 5645 - Mathematical Methods for Data Science 3 credit(s)
STAT 5650 - Statistical Learning and Data Mining I 2 credit(s)
STAT 5685 - Deep Learning Theory and Applications 3 credit(s) or
STAT 6685 - Deep Learning Theory and Applications 3 credit(s)