Computer Information Systems (CIS)
CIS 512 INTRODUCTION TO DATA SCIENCE AND ANALYTICS
3, 3/0
Prerequisites: Graduate standing. Introduction to Data Science and Analytics; modern analytical techniques; application to academia, industry and business needs. Fundamental concepts and terms; methods, tools, and techniques; identification of “big data” problems; data sources; analytical approaches; algorithm implementations; interpretation and reporting of results. Offered annually in the Fall semester.
CIS 590 INDEPENDENT STUDY
1-3, 0/0
Graduate independent study in Computer Information Systems.
CIS 594 GRADUATE WORKSHOP
1-3, 0/0
Graduate workshop in Computer Information Systems.
CIS 600 MACHINE LEARNING FOR DATA SCIENCE
3, 3/0
Prerequisites: CIS 512 or DSA 512 or equivalent. Introduction to Machine Learning Techniques for Data Science; mathematical methods; algorithms; application to academia, industry and business problems. Fundamental concepts and terms; methods, tools, and techniques. Supervised and unsupervised learning; identification of learning problems; data sources; analytical approaches; algorithm implementation; interpretation and reporting. Offered annually in the Fall semester.
CIS 690 MASTERS PROJECT IN EDUCATIONAL COMPUTING
3, 3/0
A project undertaken by one or more individuals on a problem of special interest within Computer Information Systems, planned and carried out with consultation and guidance from the instructor.
CIS 695 MASTERS THESIS
3, 6/0
Individual investigation of an original problem within Computer Information Systems submitted in acceptable form according to directions given by the Graduate School.
CIS 721 THESIS/PROJECT CONTINUATION
0, 0/0
CIS 722 THESIS/PROJECT EXTENDED
0, 0/0