Courses
Multivariate Analysis and Stochastic Models
In the first part, the course includes: Experimental design, statistical estimation and hypothesis testing from multivariate distribution. Topics covered will include: regression models, multivariate analysis of variance, canonical correlations, classification procedures and factor analysis. Computer applications of these techniques will be examined. In the second part, the course covers an
Graduate Internship
The graduate internship is designed to provide doctoral students with more opportunity to test and experiment in industry, research organizations, government agencies, and other appropriate experiential venues associated with technology utilization, transfer, and innovation for the explicit purpose of developing knowledge in the specialization. A personal assessment portfolio will be developed as
Research Seminars
The Ph.D. student will do at least two research seminars on advanced topics related to MOT. Topic will be chosen by the student and approved by his supervisor. Topic could be related and/or complementary to her/his dissertation. Seminars will be attended by University faculty, students and external audience.
Directed Advanced Studies
In this course, students follow in-depth directed study in a given topic or field of their choice under the close supervision of a faculty member. The topic should be of advanced nature, perhaps in emerging technologies or alike. A student may repeat the course for credit provided that the topic or field of choice is different. Repeating the course for credit requires the approval of the program
Advanced Topics in Management of Technology
This course is tailored to expose students to the latest advances in fields that are related to their specialization in management of technology, and/or to focus on a specific area of particular interest to the discipline. Course contents may vary from term to term to address emerging subjects.
Advanced topics in Quality, Reliability and Maintainability
The course introduces the concepts of quality and total quality management and their applications. It also covers Quality models, International standards (ISO 9000) series and its applications in industrial field, Statistical Process Control (SPC), and practical applications of total quality management. This course, also, introduces concepts, principles and techniques used in evaluation and
Projects Risk Assessment and Management
This course introduce the students to the risks that affect the performance objectives across all organizational activities, whether these be strategic, program, project or operational. It gives the students a useful insight of the concepts, processes, and methods of risk management in projects and the inextricably link between value management and risk management. The student will gain the skills
Contemporary Issues in Information Technology
This course investigates a number of contemporary issues in the rapidly changing information technology environment. Considerations of social and ethical issues in information technology. It also investigates in depth a number of topical theoretical issues and practical information technology tools and broadens students' perspective and skills. It includes: The effects of information technology on
Supply Chain Management
Supply Chain Management is a business model necessary for an organization's success and everyone in the organization needs to be involved. This course introduces the concepts of logistics and supply chain management. It discusses the complexity created by ever increasing customer requirements and expectations, globalization, the pressure on cost, and the availability and access to resources. It
Parametric and non-Parametric Statistics
This course describes and compares parametric and non parametric statistics. Models of both types are discussed and compared. The course includes: Chi-square distribution, Chisquare goodness-of-fit test for equal & non-equal expected frequencies, contingency table, nominal level of measurement, nonparametric or distribution-free tests, Kruskal-Wallis oneway analysis of variance by ranks, sign test
Systems Modeling and Simulation
The course covers the art and science of modeling and simulation in engineering /business and IT. This course blends theory with practice presenting actual applications in manufacturing as well as business and services. The course addresses the classical methodology and techniques with emphasis on discrete systems modeling and simulation. Topics include major aspects of modeling and techniques of
Emerging Technologies & Advanced MOT
This course discusses emerging technologies, their evolvement, the effect of international, political, social, economic and cultural factors. Topics covered in the course include accuracy in forecasting of past technologies, how to improve them, international perspective on emerging technologies, future customer trends and forecasting methodologies. Emerging technologies will be examined through
Advanced Production Engineering Management
This course introduces the students to the advanced production engineering management, how the firms can benefit and enhance its competitiveness, the adoption of Advanced Manufacturing Technologies (AMT), the way that firms should plan for and implement them, and their eventual performance. It will expose the students to advanced concepts in production engineering, design and innovation lifecycle
Quantitative Analyses for Managers
This course introduces the student to the techniques of mathematical programming for linear and non-linear optimization. The course discusses the various methods and models for linear programming and integer linear programming, and some coverage of non-linear methods. Probability theory and distributions are discussed and combined with decision analysis and making processes. The course exposes the
Emerging Economies
The aim of this course is to develop the analytical skills required to understand current issues and policy debates regarding emerging markets. To achieve this goal the course provides a blend of theory and policy discussions. Theoretical analysis will pinpoint relevant variables and their interaction; while policy discussions will apply the analytical tools to real world events and problems.