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 Bachelor’s Degree (First Cycle)
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
Major Area Courses
Supportive Courses X
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 Acquires sufficient knowledge in mathematics, natural sciences, and related engineering disciplines; gains the ability to use theoretical and applied knowledge in these fields in solving complex engineering problems.
2 Gains the ability to identify, define, formulate, and solve complex engineering problems; acquires the skill to select and apply appropriate analysis and modeling methods for this purpose. X
3 Gains the ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions, and applies modern design methods for this purpose.
4 Develops the skills to develop, select, and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in industrial engineering applications; gains the ability to effectively use information technologies. X
5 Gains the ability to design experiments, conduct experiments, collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics. X
6 Acquires the ability to work effectively in intra-disciplinary and multidisciplinary teams, as well as individual work skills.
7 Acquires effective oral and written communication skills in Turkish; at least one foreign language proficiency; gains the ability to write effective reports, understand written reports, prepare design and production reports, make effective presentations, and give and receive clear instructions.
8 Develops awareness of the necessity of lifelong learning; gains the ability to access information, follow developments in science and technology, and continuously renew oneself.
9 Acquires the consciousness of adhering to ethical principles, and gains professional and ethical responsibility awareness. Gains knowledge about the standards used in industrial engineering applications.
10 Gains knowledge about practices in the business life such as project management, risk management, and change management. Develops awareness about entrepreneurship and innovation. Gains knowledge about sustainable development.
11 Gains knowledge about the universal and social dimensions of the impacts of industrial engineering applications on health, environment, and safety, as well as the problems reflected in the engineering field of the era. Gains awareness of the legal consequences of engineering solutions.
12 Gains skills in the design, development, implementation, and improvement of integrated systems involving human, material, information, equipment, and energy. X
13 Gains knowledge about appropriate analytical and experimental methods, as well as computational methods, for ensuring system integration.

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