| Course Type | Elective Course |
|---|
| Course Level | Master's Degree With Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Learn different management roles and decision types
- Learn the rational decision making process
- Understand the status of DSS in Business
- Apply techniques such as Linear Programing, Decision Trees, Simulation, and Data Mining to solve simple problems by hand or using a tool
- Learn different types of DSS and enabling technologies: Group Support Systems, Expert Systems, Business Performance Management
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | |
|---|
| Course Description | This course focuses on the use and application of information systems to support the decision-making process. Knowledge-based systems, neural networks, expert systems, electronic meeting systems, group systems and web-based systems are discussed as a basis for designing and developing highly effective decision support systems. Data models, interactive processes, knowledge-based approaches and integration with database systems are also described. Theoretical concepts are applied to real-world applications. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Decision support systems and business intelligence |
|
2nd Week |
Decision Making, Systems, Modeling, and Support |
|
3rd Week |
Decision Support Systems Concepts, Methodologies, and Technologies |
|
4th Week |
Modeling and analysis |
|
5th Week |
Data Mining for Business Intelligence |
|
6th Week |
Artificial neural networks |
|
7th Week |
Text and web mining |
|
8th Week |
Midterm |
|
9th Week |
Data warehousing |
|
10th Week |
Business Performance Management |
|
11th Week |
Collaborative Computer-Supported Technologies and Group Support Systems |
|
12th Week |
Knowledge management |
|
13th Week |
Artificial Intelligence and Expert Systems |
|
14th Week |
Management support systems |
|
| Recommended or Required Reading | Efraim Turban & Jay E. Aronson. Decision Support Systems and Intelligent Systems (6th Edition) |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Discussion
- Questions/Answers
- Presentation
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
20 |
| Other |
4 |
40 |
| Total(%) |
|
60 |
| Contribution of In-term Studies to Overall Grade(%) |
|
60 |
| Contribution of Final Examination to Overall Grade(%) |
|
40 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
3 |
3 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
3 |
42 |
| Preparation for Final exam |
1 |
60 |
60 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
50 |
50 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
3 |
3 |
| Homework |
|
|
|
| Presentation (including preperation) |
4 |
3 |
12 |
| Research |
4 |
20 |
80 |
| Total Work Load | 292 |
| Total Work Load / 30 (h) | 9.73 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
