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
CIS 594 GRADUATE WORKSHOP
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
CIS 695 MASTERS THESIS
CIS 721 THESIS/PROJECT CONTINUATION
CIS 722 THESIS/PROJECT EXTENDED