Faculty : Faculty of Engineering and Applied Sciences
School : Industrial and Manufacturing Engineering
Prerequisit Course : No Pre-Requisit Courses
Credit Hours : 3.00
Offered For : Post Graduate
Course Description :
Accounting Cycle – Financial Statements –
Accounting Systems – Cash – Receivables – Fixed Assets – Current Liability – Allocation of cost – The balanced scorecard.
IEM526 - Marketing for Engineers
Faculty : Faculty of Engineering and Applied Sciences
School : Industrial and Manufacturing Engineering
Prerequisit Course : No Pre-Requisit Courses
Credit Hours : 3.00
Offered For : Post Graduate
Course Description :
Marketing concepts and principles – Margins and profits- product and portfolio management – Pricing strategy – Promotions – Marketing and finance – Distribution strategy.
IEM531 - Operations Research
Faculty : Faculty of Engineering and Applied Sciences
School : Industrial and Manufacturing Engineering
Prerequisit Course : No Pre-Requisit Courses
Credit Hours : 3.00
Offered For : Post Graduate
Course Description :
Linear Programming – Linear programming formulations – cases of linear programming- solution procedures - post optimality analysis – Integer Programming - non linear programming – Goal Programming.
IEM532 - Applied Simulation Modeling and Analysis
Faculty : Faculty of Engineering and Applied Sciences
School : Industrial and Manufacturing Engineering
Prerequisit Course : No Pre-Requisit Courses
Credit Hours : 3.00
Offered For : Post Graduate
Course Description :
Review of basic probability and statistics – basic simulation modeling – modeling complex systems -simulation software – building simulation models – selecting inputs distributions – output data analysis
IEM533 - Applied Multivariable Data Analysis
Faculty : Faculty of Engineering and Applied Sciences
School : Industrial and Manufacturing Engineering
Prerequisit Course : No Pre-Requisit Courses
Credit Hours : 3.00
Offered For : Post Graduate
Course Description :
Regression – Linear models and experimental design – Simple and multiple linear regression – single- and multi-factor studies – Analysis of variance – Analysis of covariance – Model selection – Diagnostics – Data analysis using statistical software.
