Department of Mathematics and Statistics

Minor in Data Science

The curriculum of the Minor in Data Science is designed to impart the fundamental principles and core methodology of the discipline to enrolled students. Recent advances in technology have revolutionized data acquisition and analysis across industries. The challenges and opportunities of modern data analysis have come to define data science as a discipline and require a unique skill set. The balanced instructional approach of this program to the mathematical, statistical, and computational aspects of data science meets those requirements and provides students with the analytical and technical framework sought both in industry and graduate programs across the sciences.

Minimum number of credits required for the certificate: 21

Required Courses: (15 credits)

Note: Some of these courses have prerequisites; see course descriptions.

MAT 281 Introduction to Probability (3 cr)
MAT 282 Statistical Inference (3 cr)
MAT 486 Introduction to Big Data Analytics (3 cr)
MAT 488 Introduction to Data Mining (3 cr)
MAT 496 Introduction to Data Science (3 cr)

Mathematics and Statistics Electives

Choose one course from the following:
MAT 295 Linear Algebra (4 cr)
MAT 485 Introduction to Applied Regression (3 cr)

Computer Science / Statistical Programming Electives

Choose one course from the following:
COS 184 Python Programming (4 cr)
COS 285 Data Structures (4 cr)
MAT 264 Statistical Software Packages (3 cr)