The online data analytics graduate certificate program offers courses in both data science and applied analytics to teach students how to mine and effectively communicate the meanings of large data sets. Courses in data science will provide an understanding of how to appropriately choose data manipulations and algorithms for effective data analysis. Courses in applied analytics will enable students to relate patterns and communicate the implications of the data for real-world situations.
Students are required to complete 12 credit hours from the list of approved courses below plus a 3-credit-hour capstone course. Each student is required to take at least one course from each section to ensure that they are gaining a background in both data science and applied analytics. Additional credits may be earned from the selection of elective courses.
In accordance with university policy, students may transfer no more than 5 graduate credit hours from another school to their graduate certificate program. Transfer credits must be approved by the student's advisor.
Data Science Courses
- CIS 730 - Principles of Artificial Intelligence (Fall terms)
- CIS 732 - Machine Learning and Pattern Recognition (Spring terms)
- CIS 734 - Introduction to Genomics and Bioinformatics (TBD)
- CIS 833 - Information Retrieval and Text Mining (Fall terms)
- MATH 725 - The Mathematics of Data and Networks I (TBD)
- MATH 726 - The Mathematics of Data and Networks II (TBD)
- STAT 705 - Regression and Analysis of Variance (Fall and Spring terms)
- STAT 730 - Multivariate Statistical Methods (Fall and Spring terms)
Applied Analytics Courses
- IMSE 785 - Big Data Analytics (Spring, odd years; Summer, even years)
- MIS 665 - Business Analytics and Data Mining (Fall term)
- MIS 670 - Social Media Analytics and Web Mining (Spring term)
- MKTG 880 - Advanced Business Intelligence for Strategic Decision Making (Spring term)
- MKTG 881 - Applied Business Data Analytics (Fall term)
- GENBA 894 - Data Analytics Capstone (Summer term)
All coursework is offered at a distance via K-State Online, the course management system at Kansas State University. Classes are made up of readings, videos, discussion boards and other online learning activities. Classes vary in format. Students may work on group projects using appropriate digital media tools or independently, yet share comments and questions via K-State Online.
Courses are delivered within a semester time frame and may be eight-week or 16-week classes. Summer classes are four to 12 weeks.