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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.

Required Courses (28 hours)

DAT/CSC 472	Introduction to Database Systems
DAT 502	Introduction to Statistical Computation
DAT 530	Advanced Statistical Methods
DAT/CSC 532	Introduction to Machine Learning
DAT/CSC 533	Data Mining
DAT/CSC 534	Big Data Analytics
DAT 554	Data Analytics Capstone ¹

Electives (choose two courses)

DAT 444	Operations Research Methods
or MAT 444	Operations Research Methods
DAT 570/CSC 535	Advanced Topics in Data Analytics (Deep Learning)
CSC 561	NoSQL Databases
CSC 562	Data Visualization
CSC 572	Advanced Database Concepts

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.