Decision Support Systems (IE514) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Decision Support Systems IE514 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives In this course, the students will be learning fundamental concepts of decision support systems to be able to apply for their practical problems.
Course Learning Outcomes The students who succeeded in this course;
  • Students will learn fundamental concepts of decision support systems.
  • Students will have an insight about the role of decision support systems for industrial engineering discipline.
  • Students will evaluate and solve real life processes and problems using decision support systems.
  • Students will design and develop decision support systems.
Course Content Decision support systems and business intelligence, decision making, systems, modeling and support, decision support systems concepts, methodologies and technologies, modeling and analysis, data warehousing, business analytics and data visualization, data, text and web-mining, neural networks for data mining, business performance management, collab

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to Decision Support Systems
2 Decision Support Systems and Business Intelligence
3 Decision Making, Systems, Modeling and Support
4 Decision Support Systems Concepts, Methodologies and Technologies
5 Modeling and Analysis
6 Data Warehousing
7 Business Analytics and Data Visualization
8 Data, Text and Web-Mining
9 Business Performance Management
10 Collaborative Computer-Supported Technologies and Group Support Systems
11 Midterm
12 Knowledge Management
13 Artificial Intelligence and Expert Systems
14 Advanced Intelligence Systems
15 Decision Support System Applications
16 Final Examination Period

Sources

Course Book 1. Turban E., Aranson J.A., Liang T.P., Decision Support Systems and Intelligent Systems, Pearson Educational International, 2005 Seventh Edition
Other Sources 2. Mora M., Forgionne G., Gupta N.D.J., Decision Making Support Systems Achievements and Chalanges for the New Decade, IDEA Group Publishing, 2003, London.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project 1 30
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 40
Toplam 3 100
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Ability to carry out advanced research activities, both individual and as a member of a team
2 Ability to evaluate research topics and comment with scientific reasoning
3 Ability to initiate and create new methodologies, implement them on novel research areas and topics
4 Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions
5 Ability to apply scientific philosophy on analysis, modelling and design of engineering systems
6 Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level
7 Contribute scientific and technological advancements on engineering domain of his/her interest area
8 Contribute industrial and scientific advancements to improve the society through research activities

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 1 16
Presentation/Seminar Prepration
Project 1 4 4
Report
Homework Assignments 4 4 16
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 16 16
Prepration of Final Exams/Final Jury 1 25 25
Total Workload 125