Master of Data Science

Collaborative program with the Department of Computer Science

This professional master’s degree program consists of 33 credit hours of coursework including a six credit hour practicum project. The program is designed primarily for those with previous degrees or experience in computer science, statistics, mathematics, the natural or social sciences, or business, and who are interested in preparing for a career as a data science professional in business and industry. Full-time students may complete the program in one year, including one summer term.

Admission Requirements

Applicants should have a bachelor’s degree from an accredited university with a minimum cumulative GPA of 3.0/4.0. A combined verbal and quantitative GRE examination score of at least 304 and an analytical writing score of at least 3.0 are required. The GRE requirement may be waived for students with a bachelor’s degree from an accredited college or university in the United States with a cumulative GPA of at least 3.0/4.0.

Prerequisites include knowledge of a high level programming language at the level of CS 201 (object-oriented programming is required), a data structures and algorithms course at the level of CS 331, multivariate calculus at the level of MATH 251, linear algebra at the level of MATH 332, and probability and statistics at the level of MATH 474. Information on these courses is available in this bulletin. Proficiency and placement exams are also available.

Students with an insufficient background in computer science and/or mathematics will be required to take the relevant prerequisite courses and earn at least a "B" grade in each. These prerequisite courses do not count toward the 33 credit hour requirement.

Curriculum

Coursework includes 18 credit hours of required core courses, nine credit hours of elective courses, and six credit hours of CSP 572 Data Science Practicum. At least nine credit hours must be taken of 400- or 500-level CS or CSP courses and nine credit hours of 400- or 500-level MATH courses, not including the CSP 572 Data Science Practicum.

Up to six credit hours of 400-level undergraduate coursework may be used toward degree requirements.

Data Science Core Courses (15)
MATH 563Mathematical Statistics3
or MATH 564 Applied Statistics
CS 584Machine Learning3
or MATH 569 Statistical Learning
SCI 511Project Management3
or SCI 522 Public Engagement Scientists
CSP 571Data Preparation and Analysis3
Select a minimum of one course from the following:3
Advanced Database Organization3
Data-Intensive Computing3
Big Data Technologies3
Data Science Capstone (6)
CSP 572Data Science Practicum6
Data Science Electives (12)
Select 9 to 12 credit hours of Data Science Electives12
Total Credit Hours33

Data Science Electives

Computational Fundamentals
Database Organization3
Introduction to Algorithms3
Operating Systems3
Data Integration Warehousing3
Advanced Database Organization3
Data Privacy and Security3
Dsgn and Anlys of Algorithms3
Parallel and Distributed Proc3
Cloud Computing3
Data-Intensive Computing3
Software Testing and Anlys3
Big Data Technologies3
Computer Science Applications
Data Mining3
Computer Vision3
Geospatial Vision/Visualizatio3
Advanced Data Mining3
Information Retrieval3
Cyber-Physical Sys: Lang & Sys3
Cyber-Physical Sys Sec/Dsgn3
Deep Learning3
Interact/Trans Mach Learning3
Online Social Network Analysis3
Advanced Artificial Intelligen3
Probabilistic Graphical Models3
Machine Learning3
Natural Language Processing3
Mathematics, Probability, and Statistics
Graph Theory and Applications3
Intro to Stochastic Processes3
Design and Analysis of Exprmnt3
Mathematical Modeling I3
Mathematical Modeling II3
Mathematical Modeling3
Linear Algebra3
Optimization I3
Probability3
Stochastic Processes3
Introduction to Time Series3
Monte Carlo Methods in Fin3
Multivariate Analysis3
Adv Design of Experiments3
Statistical Learning3
Machine Learning in Finance:3
Bayesian Computational Stats3
Mathematical and Scientific Computing
Bioinformatics3
Computational Mathematics I3
Computational Mathematics II3
Meshfree Methods3
Computational Physics3
Professional Skills
Project Management3
Public Engagement Scientists3
Fundamentals of Design3
User Experience Research/Eval3

Master of Data Science Curriculum

Year 1
Semester 1Credit HoursSemester 2Credit HoursSemester 3Credit Hours
CS 525, 554, or CSP 5543CS 584 or MATH 5693CSP 5726
MATH 563 or 5643CSP 5713 
SCI 511 or CS 5873Data Science Elective3 
 9 9 6
Year 2
Semester 1Credit Hours  
SCI 5223  
Data Science Elective3  
Data Science Elective3  
 9
Total Credit Hours: 33