Program Administration

The Data Analytics certificate is a cooperative interdisciplinary program of the colleges of Business Administration, Arts and Sciences, and Engineering.  The College of Business Administration serves as the academic home for the program, coordinating administration of the program and providing administrative support. 

Academically, the program is governed by a steering committee with representatives from the participating departments, currently Computing and Information Sciences, Industrial and Manufacturing Systems Engineering, Management, Marketing, Mathematics, Statistics, and Global Campus. 

Two faculty, one with an applied analytics focus and the other with a focus on data science, serve as advisors for the program. The advisors provide curriculum leadership, respond to student inquiries, evaluate student admissions, advise students and develop plans of study, as well as other academic related tasks.  All correspondence should be directed to the College of Business Administration.

Program Requirements:

The Graduate Certificate in Data Analytics consists of 15 credit hours.

Students will be required to complete 12 credit hours from the list of approved courses below plus a 3-credit-hour capstone course. Each student will be required to take at least one course from each area to ensure that they are gaining background in both data science and applied analytics. Additional credits may be earned from the selection of elective courses.

• CIS 730 - Principles of Artificial Intelligence Credits: 3
• CIS 732 - Machine Learning and Pattern Recognition Credits: 3
• CIS 734 - Introduction to Genomics and Bioinformatics Credits: 4
• CIS 833 - Information Retrieval and Text Mining Credits: 3
• ECE 841 - Network Theory Credits: 3
• IMSE 785 - Big Data Analytics Credits: 3
• MATH 725 - The Mathematics of Data and Networks I Credits: 3
• MATH 726 - The Mathematics of Data and Networks II Credits: 3
• STAT 705 - Regression and Analysis of Variance Credits: 3
• STAT 730 - Multivariate Statistical Methods Credits: 3

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• Courses in Applied Analytics

• IMSE 785 - Big Data Analytics Credits: 3
• MIS 665 - Business Analytics and Data Mining Credits: 3
• MIS 670 - Social Media Analytics and Web Mining Credits: 3
• MKTG 880 - Applied Marketing Analytics Credits: 3
• MKTG 881 - Advanced Marketing Analytics Credits: 3

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• Capstone Course

• GENBA 894 - Data Analytics Capstone Credits: 3

Total hours required: 15