Decision Support Systems (IE444) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Decision Support Systems IE444 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
  • Instructor Dr. Uğur Baç
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, business performance management, decision support system applications

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Decision Support Systems and Business Intelligence
2 Decision Making, Systems, Modeling and Support
3 Decision Support Systems Concepts, Methodologies and Technologies
4 Modeling and Analysis
5 Data Warehousing
6 Business Analytics and Data Visualization
7 Business Analytics and Data Visualization
8 Text and Web-Mining
9 Business Performance Management
10 Business Performance Management
11 Interactive Computer Based Technologies
12 Decision Support System Applications
13 Decision Support System Applications
14 Decision Support System Applications
15 Final Examination Period
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, 7th Edition, 2005.
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, London, 2003.

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 2 30
Final Exam/Final Jury 1 40
Toplam 4 100
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 apply the acquired knowledge in mathematics, science and engineering
2 Ability to identify, formulate and solve complex engineering problems X
3 Ability to accomplish the integration of systems
4 Ability to design, develop, implement and improve complex systems, components, or processes
5 Ability to select/develop and use suitable modern engineering techniques and tools X
6 Ability to design/conduct experiments and collect/analyze/interpret data X
7 Ability to function independently and in teams
8 Ability to make use of oral and written communication skills effectively
9 Ability to recognize the need for and engage in life-long learning
10 Ability to understand and exercise professional and ethical responsibility
11 Ability to understand the impact of engineering solutions
12 Ability to have knowledge of contemporary issues

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 10 1 10
Presentation/Seminar Prepration
Project 1 30 30
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 15 15
Prepration of Final Exams/Final Jury 1 22 22
Total Workload 125