Information Package / Course Catalogue
| Course Code | : BYP241 |
| Course Type | : Area Elective |
| Couse Group | : Short Cycle (Associate's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 2 |
| Prt. | : 1 |
| Credit | : 3 |
| Lab | : 0 |
| ECTS | : 3 |
The main objective of the Digital Decision Support Systems course is to equip students with the skills to transform data into strategic information, analyze complex managerial problems, and make the most accurate decisions quickly using computer-based tools.
The Digital Decision Support Systems course covers the processes of collecting, modeling, and analyzing data using business intelligence tools to solve management problems. Throughout the course, practical applications are explored on how to make the most optimal and fastest decisions using artificial intelligence and simulation-supported computer-based systems.
| 1. | They can identify managerial and strategic problems in businesses; and conceptually analyze the database, model, and interface components of a Decision Support System. |
| 2. | By processing raw corporate data, it can design interactive dashboards and reports that facilitate executive decision-making using modern business intelligence tools like Power BI or Tableau. |
| 3. | To find the optimal solution in situations of uncertainty and risk, quantitative models such as linear programming, "what-if" analyses, and sensitivity analyses can be applied in a computer environment. |
| 4. | This study can explain and demonstrate how artificial intelligence approaches, such as prediction, machine learning, and expert systems, can be used as leverage in businesses' strategic decisions for the future. |
| 5. | They can develop data-driven, rational, and competitive strategies to solve complex problems in the business world; while respecting data privacy (KVKK) and ethical rules. |
| 1. | Business Intelligence and Decision Support Systems, Prof. Dr. Şeref Sağıroğlu, Dr. Halil İbrahim Bülbül |
| 2. | Data Mining Approaches in the Decision-Making Process, Dr. Ömer Akgöbek |
| 3. | Multi-Criteria Decision-Making Methods, Prof. Dr. Metin Dağdeviren, Dr. Serkan Yıldırım |
| Type of Assessment | Count | Percent |
|---|---|---|
| Practice | 1 | %15 |
| Term Assignment | 1 | %5 |
| Midterm Examination | 1 | %20 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 0 | 2 | 28 |
| Lecture - Practice | 14 | 0 | 1 | 14 |
| Assignment | 1 | 2 | 0 | 2 |
| Individual Work | 4 | 0 | 2 | 8 |
| Practice Examination | 1 | 5 | 1 | 6 |
| Midterm Examination | 1 | 6 | 1 | 7 |
| Final Examination | 1 | 9 | 1 | 10 |
| TOTAL WORKLOAD (hours) | 75 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | |
OÇ-1 | 5 | 3 | 3 | 2 | 4 |
OÇ-2 | 3 | 5 | 5 | 3 | 5 |
OÇ-3 | 3 | 4 | 5 | 2 | 5 |
OÇ-4 | 4 | 5 | 4 | 2 | 5 |
OÇ-5 | 4 | 4 | 5 | 4 | 5 |