MS in Data Science
Students may be admitted in full graduate standing to the MS in data science program if they have a bachelor’s degree in computer science or any related engineering discipline (please see required topics below), a GPA of at least 3.000, and also meet the Graduate School’s other requirements. Students who have a bachelor’s degree in other quantitative disciplines (mathematics, physics or other disciplines) with demonstrated quantitative skills (calculus, linear algebra, etc.) and proficiency in computer programming may be admitted on a conditional basis.
Application materials will be reviewed by the Graduate School and the MS in data science graduate coordinator, after which the student will be notified of their decision. Students entering the MS in data science program are expected to have already completed courses in programming, linear algebra, statistics and data structures. If prior coursework deficiencies exist, then the student may be admitted on a conditional basis. It is recommended that deficiencies are completed prior to beginning graduate studies.
|CS 746||Perspectives on Data Science||3|
|BSAN 775||Perspectives on Business Analytics||3|
|MATH 746||Introduction to Data Analytics||3|
|CS 697AB||Machine Learning||3|
|CS 896||Capstone Project in Data Science||3|
|Data Science Elective Courses|
|Select 9 credit hours from the list of classes below.||9|
|Introduction to Database Systems|
|Introduction to Bioinformatics|
|Deep Learning: Theory, Algorithms and Applications|
|Algorithmic Technicques for Big Data Analysis|
|Advanced Topics in Machine Learning|
|Introduction to Intelligent Robotics|
|Image Analysis and Computer Vision|
|Artificial Intelligence for Robotics|
|Discipline Elective Courses|
|Select 6 credit hours from the list of classes below.||6|
Any of the courses listed in Data Science Electives.
|Business Intelligence and Analytics|
|Applied Regression Analysis|
|Analysis of Variance|
|Applied Statistical Methods II|
|Neural Networks and Machine Learning|
|Bayesian Statistics and Uncertainty Quantification|
|Analytics and Decision Making In Sport|
|Big Data Analytics in Engineering 1|
|Introduction to Data Mining and Analytics 2|
|Database Planning & Management|
|Advanced Business Analytics|
|Total Credit Hours||30|
If CS 898AJ not taken.
If CS 898D not taken.
Students in the MS in data science program are required to complete an applied learning or research experience to graduate from the program. The requirement can be met by completing the mandatory course CS 896 Capstone Project in Data Science.