MIS PhD Courses

 

 

The required courses for the MIS PhD program are listed below. In addition, students must register for 18 credits of MIS 920 (Dissertation).

This course introduces the student to fundamentals of database analysis, design and implementation. Emphasis is on practical aspects of business process analysis and the accompanying database design and development. Topics covered include: conceptual design of databases using the entity relationship model, relational design and normalization, SQL and PL/SQL, web based database design and implementation using Oracle or some other modern Database Management Systems. Students are required to work with a local client organization in understanding their business requirements, developing a detailed set of requirements to support business processes and designing and implementing a web based database application to support their day- to-day business operations and decision making. Students will acquire hands-on-experience with a state-of-the-art database management system such as Oracle or Microsoft SQLServer, and web-based development tools. This course is also offered online.

Prerequisite: MIS 541 or consents of instructor
Units: 3

This course is designed to introduce fundamental statistical principles and modern applied machine learning techniques. The first part will cover the basics of classical probability theory and statistical inference. The second part will introduce statistical learning, with particular attention paid to R implementations. Examples are drawn from marketing, finance and other areas for illustration. 

Units: 3

Introduces beginning doctoral degree students and advanced master's degree students to important research and survey articles in the field of management information systems.

Units: 3

Provides a knowledge of research methodologies used in the MIS discipline, including experimental design, surveys, case studies, field work and software engineering.

Units: 3

This full semester class will meet once a week for 2.5-3 hours. The objective of this class is to introduce second year MIS PhD students to research in the economics of information systems. The class will organized into three parts: (1) overview of economics of IS core concepts and historically major themes of research, (2) commonly used methodologies in Econ of IS research (econometrics, analytical models, experiments and newer approaches) and (3) contemporary themes and research topics.

This will be a readings and discussion class, with heavy emphasis on both reading and discussion and four-to-six research articles assigned for readings every week. Students will be expected to read and digest every article discussed in class. Class periods will focus heavily on student-run discussions. By the end of the semester, students in this class should be confident in their ability to review Econ of IS papers, pursue Econ of IS research projects, know what courses they should take to develop further expertise and have produced at least one work-in-progress research paper in economics of information systems.

Units: 3

This PhD level course aims to provide the foundation and knowledge in state-of-the-art data, text and web mining research for various structured, unstructured and web-based, data-centric applications. Students will become familiar with key data, text and web mining computational methods and techniques. They will also learn to apply such analytical techniques and related methodologies in advanced business, scientific or web research.

Units: 3

The development and exchange of scholarly information, usually in a small group setting. The scope of work shall consist of research by course registrants, with the exchange of the results of such research through discussion, reports and/or papers. 

Units: 3

The development and exchange of scholarly information, usually in a small group setting. The scope of work shall consist of research by course registrants, with the exchange of the results of such research through discussion, reports and/or papers. Course will cover basic computational complexity terminology, machine scheduling concepts and linear programming leading to column generation methodology.

Units: 3

Qualified students working on an individual basis with professors who have agreed to supervise such work. Graduate students doing independent work which cannot be classified as actual research will register for credit under course number 599, 699 or 799.

Course can qualify for 1 to 6 credits.

Units: 1-6

Research for the doctoral dissertation (whether library research, laboratory or field observation or research, artistic creation or dissertation writing).

Units: 18