ISE 500 - Intelligent Systems Engineering Seminar:

This course aims to provide a series of seminars o the state of the art research topics in the area of Intelligent Manufacturing and Decision Systems Engineering, to get acquainted with recent literature in these topics and discuss the literature.

ISE 501 - Mathematical Modeling and Applications:

This course presents how to optimize engineering problems by formulating through mathematical programming and solving with different tools used in this area. Linear programming theory and applications, formulations, graphical solution and simplex algorithm, duality and sensitivity analysis and transportation and assignment problems, integer programming and network problems, algorithms and solution techniques are the main subjects covered in this course.

ISE 511 - Decision Making:

This course provides an overview of decision analysis for master's degree students. Modern up-to-date decision analysis techniques are provided to help a decision maker think hard about the specific problem at hand. Multi-criteria decision making techniques, decision making under risk and uncertainty, problems of multiple decision makers and game theory orientation are the main subjects covered in this course.

ISE 532 - Algorithms Design and Heuristics:

This course provides the fundamental concepts of heuristics in solving various optimization problems with emphasis on meta-heuristics.

ISE 533 - Advanced Supply Chain and Distribution Systems

This course is a comprehensive study of the concepts, processes, and models used in the design, development, analysis, and management of supply chains and distribution systems. Topics covered in this course are: inventory control, location and transportation decisions, distribution and capacity planning.

ISE 552 - Advanced Manufacturing Systems:

This course provides an overview of application of systems analysis and industrial engineering to the design, planning, and analysis of manufacturing systems. Principal topics include the general structure of CIM systems, data networks, robotics, CNC machinery and quality control systems.

ISE 557 - Data Structures and Algorithms:

This course covers the basic science behind the use of computers to provide effective and efficient methods for carrying out tasks. Tasks examined include data storage and retrieval, sorting and searching, semi-numerical tasks such as encryption, planning and optimization tasks, problems, space searches and games playing. To carry out these tasks, both algorithms and structures for the storage of data need to be specified. Mathematical tools have to be developed that enable us to measure the fundamental effectiveness of algorithms and in particular the way these algorithms scale as the size of the task being performed increases. This course introduces the basic sorting and searching methods and dynamic data structures such as linked lists, trees and hash tables.

ISE 561 - Artificial Intelligence

Artificial Intelligence aims at modeling and analysis of rational behavior based on information. Common theme in AI fields is creation of "intelligent" agents and machines. This course provides an introduction to problem solving techniques that introduce intelligent behavior into agents/computers, information representation, inference, perception and interpretation. The course reflects this variety of subjects, and discovers essential techniques by studying basic problems and issues of AI. This course is project based, and assignments throughout the semester uses Common LISP and Prolog languages.

ISE 572 - Data Mining:

This course will explore current data mining concepts also known as knowledge discovery from data Or KDD shortly. It focuses on fundamental data mining techniques for learning the rules or identifies the patterns from a given data. In this course, the students are expected to propose their own proposal, do implementation or apply some built-in library and evaluate the results.

ISE 581 - Graph Theory:

Graphs are excellent tools to represent relational phenomenon in the real world. Modeling of a real world scenario with graph based structure and applying graph algorithms to solve the actual problem is a common method. This course covers subjects as wide as shortest path algorithms to proof of Brooks and Chytal, and invites students to abstract over graphs.