Online
The Curriculum
Students must complete 28 required credit hours and eight elective credit hours to earn the Data Analytics degree while maintaining a minimum GPA of 3.0 on a scale of 4.0 as listed below.
** Admissions to the online program will not be granted to international students residing outside of the U.S.
Required Courses (28 hours)
| CSC 472 | Introduction to Database Systems | 4 |
| DAT 502 | Introduction to Statistical Computation | 4 |
| DAT 530 | Advanced Statistical Methods | 4 |
| CSC 532 | Introduction to Machine Learning | 4 |
| CSC 534 | Big Data Analytics | 4 |
| CSC 535 | Deep Learning | 4 |
| DAT 554 | Data Analytics Capstone 1 | 4 |
Electives (choose two courses)
| DAT 444 | Operations Research Methods | 4 |
| or MAT 444 | Operations Research Methods | |
| CSC 533 | Data Mining | 4 |
| CSC 561 | NoSQL Databases | 4 |
| CSC 562 | Data Visualization | 4 |
| CSC 572 | Advanced Database Concepts | 4 |
| CSC 570 | Advanced Topics in Computer Systems (Containerization/BigData or A.I. for Cybersecurity) | 4 |
| 1 |
The capstone project will draw upon the knowledge and skills learned throughout the entire curriculum and will ask students to apply the appropriate methods and tools for data analysis in a real-world organizational setting. The capstone course provides the opportunity to exercise different techniques for data storage, preprocessing, integration and analysis covered throughout the M.S. in Data Analytics curriculum in order to address business challenges. The students must provide a well-written report and an oral presentation to effectively communicate their findings. |