Information Technology

(AIS and MSIS Departments, Rutgers Business School)


26:198:621 Electronic Commerce
Spring 2009 and every second spring thereafter.
This course will cover the theoretical foundations, implementation problems and research issues of the emerging area of electronic commerce. It will discuss technological, conceptual, and methodological aspects of electronic commerce. The list of topics to be covered in this course includes: fundamentals of Internet technology, pricing of and accounting for Internet transport, security problems of the Internet, electronic payment systems, online financial reporting and auditing, intelligent agents, web measurements, electronic markets and value chain over the Internet. The coursework will include presentations of research articles, in-class discussions, and a final course project researching one of the problems of electronic commerce. Prerequisite: basic computer literacy, introductory courses in computer information systems and economics.

26:198:622 Machine Learning
Every spring.

26:198:641 Advanced Database Systems
Every fall.
Emphasizes the functions of database administrator. Includes survey of physical and logical organization of data and their methods of accessing, and the characteristics of different models of generalized database management systems. Prerequisite: A master's-level course in databases such as 22:198:603 or NJIT CIS 631.

26:198:642 Multimedia Information Systems
Fall 2009 and every second fall thereafter.
This course covers principal topics related to multimedia information systems. These include organizing multimedia content, physical storage and retrieval of multimedia data, content-based search and retrieval, creating and delivering networked and multimedia presentations, and current research directions in this area. Prerequisite: A master's-level course in databases such as 22:198:603 or NJIT CIS 631.

26:198:643 Information Security
Fall 2008 and every second fall thereafter.

26:198:644 Data Mining
Every spring.

The key objectives of this course are two-fold: (1) to teach the fundamental concepts of data mining and (2) to provide extensive hands-on experience in applying the concepts to real-world applications. The core topics to be covered in this course include classification, clustering, association analysis, and anomaly/novelty detection.

26:198:645 Data Privacy
Fall 2009 and every second fall thereafter.

26:198:685 Special Topics in Information Systems

Data Structures and Algorithms

Big Data: Data-Intensive Analytics

Applications of Machine Learning to Big Data


26:198:686 First Early Research Seminar in Information Systems

26:198:687 Second Early Research Seminar in Information Systems

26:198:688 Independent Study in Information Systems

26:198:799 Dissertation Research in Information Systems


Please note: Links to recent syllabi are provided where possible. In some cases, the link goes to the web site for the individual faculty member, where the syllabus is maintained. In other cases, the link allows you to download the syllabus. Other syllabi are available in the Program Office.

These syllabi are provided as information to potential applicants. They should also help current students make their individual study plans. But they are subject to change. Students should not buy books or make other plans related to a course until they have confirmed with the instructor that they have an up-to-date syllabus for the semester in which they are taking the course.