Computer Information Systems (CIS)
CIS 500 MICROCOMPUTER SYSTEMS
CIS 512 INTRODUCTION TO DATA SCIENCE AND ANALYTICS
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
Graduate independent study in Computer Information Systems.
CIS 594 GRADUATE WORKSHOP
Graduate workshop in Computer Information Systems.
CIS 600 MACHINE LEARNING FOR DATA SCIENCE
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
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
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
CIS 722 THESIS/PROJECT EXTENDED