Information Systems (PhD)

Overview

PhD program in Information Systems is to prepare students with the following abilities: Understanding of the theory and application of information technology focused around the core areas of computer science, management information systems and interdisciplinary informatics. Knowledge of the analysis, design, development, and implementation of current and future information technologies; Competence in conducting and managing high-quality, basic and applied research; Solid grounding in the fundamentals of academic teaching; Strong foundation in multidisciplinary and emergent areas in information technology.

PhD in Information Systems requires that the student completes a minimum of 60 credit units.

Duration: minimum 48 months maximum 84 months

Course Descriptions

CIE 900 Model Thinking

The objective of this course is first to introduce the general concept of models. What are models? Are there different types of models? Who uses models? Why are models useful? This introduction to models also serves to discuss the concept of system, complexity, simulation and optimization. Also addressed is the role of models as tools to understand system behavior and decipher complexity. The second purpose of the course is to present and illustrate with examples of applications the main categories of models: statistical models, agent-based models, simulation models, game theory and optimization models. The third and last objective is to select one or two specific model types and practice both model building and use with real life examples of applications.

 

CIE 902 Research Directions and Methodology

This course aims to equip research students with the necessary foundations and skills to evaluate and perform qualitative research at a postgraduate level. Course Description: Three semester hours. This course offers "An overview of research methodology including basic concepts employed in quantitative and qualitative research methods. Includes computer applications for research. 

 

INF 902 Advanced Systems Analysis and Design

Methods of information systems analysis and design for service organizations with data-processing needs are studied and applied. System feasibility; requirements analysis; database utilization; Unified Modeling Language; software system architecture, design, and implementation, management; project control; and systems-level testing

 

INF 906 Database Management

This course focuses on the general concepts and methodologies in file and database management systems-data representation, data modeling and file organization.  Additional focus will be on the movement of data to related database systems within and outside the user organization.  Students are required to understand the architecture of and start implementing simple database applications using commercially available packages such as MS-ACCESS, and ORACLE.

 

INF 922 Security and Auditing of Information Systems

This course covers the technical as well as administrative aspects of security in modern digital enterprises from a total systems point of view instead of concentrating on one issue (e.g., networks security, host security, data security, cryptography). The course starts with a comprehensive overview of security principles and practice that are needed to satisfy the IS systems integrity, confidentiality and availability requirements, The course also examines the use of various standards, guidelines, laws and methods which are used in information systems audits for IS security.  This discussion serves both to set the governance framework the information systems audit works within and the choices for specific courses of action to meet the requirements of the audit

 

CIE 952 Advanced Statistics Methods

Modern Data Mining: Statistics or Data Science has been evolving rapidly to keep up with the modern world. While classical multiple regression and logistic regression technique continue to be the major tools we go beyond to include methods built on top of linear models such as LASSO and Ridge regression. Contemporary methods such as KNN (K nearest neighbor), Random Forest, Support Vector Machines, Principal Component Analyses (PCA), the bootstrap and others are also covered. Text mining especially through PCA is another topic of the course. While learning all the techniques, we keep in mind that our goal is to tackle real problems. Not only do we go through a large collection of interesting, challenging real-life data sets but we also learn how to use the free, powerful software "R" in connection with each of the methods exposed in the class.

 

ELECTIVE COURSES

 

INF 910  IT Project Management Fundamentals

This course is a study of modern methods of defining, planning and managing large IT and other business projects. Computer software and network modeling are used to support the efficient scheduling of interdependent activities.  CASE tools will be employed in this hands-on project-based individualized course.

 

CIE 912 E-Commerce

Electronic commerce is the use of computer networks to improve organizational performance. This course focuses on the study of current management issues associated with electronic commerce strategies. Emerging technologies and approaches are studied.

CIE 956-Topics in Artificial Intelligence

Introduction to topics in artificial intelligence such as problem solving methods, game playing, understanding natural languages, pattern recognition, computer vision and the general problem of representing knowledge. Students will be expected to use LISP. This will provide the foundations of Artificial Intelligence, including: Representing intelligent behavior in terms of agent, Searching a space of answers for a solution to a problem in practical time, Representing problems in terms of logic and deduction, Automated creation of complex plans in complex and unknown environments, Logical representations of uncertainty, and rational decision making in uncertain environments, Automated creation of new knowledge from examples and previous knowledge. To provide an overview of the state-of-art algorithms used in AI.

 

INF 914 Human Computer Interaction

The importance of the human-computer interface in the design and development of things that people use is the focus of this course. Topical areas  include an in-depth study of  the perceptual, cognitive, and social characteristics of people, as well as methods for learning more about the people you wish to use your systems (analyzing the tasks they perform, the way they perform them, the way they think and feel about what they do, etc.).

 

INF 916 Advanced Operating Systems

Focus of this course is on design and implementation of modern operating systems. Topics include: operating system design, virtual memory management, virtual machines, OS interaction with the hardware architecture, synchronization and communication, file systems, protection, and security.

 

INF 920 Data Mining and Data Warehouse

Data mining and investigation is a key goal behind any data warehouse effort.  The course will provide an in-depth coverage of advanced concepts on data warehousing, data mining, text mining, and web mining. Lectures and real-world examples will be used to explain the fundamental principles, uses, and some technical details of data mining techniques. The emphasis primarily is on understanding the business application of data mining techniques, and secondarily on the variety of techniques.
Admission Requirement
Tuition Fees