Information Package / Course Catalogue
| Course Code | : BİS622 |
| Course Type | : Area Elective |
| Couse Group | : Third Cycle (Doctorate Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 3 |
| Prt. | : 0 |
| Credit | : 3 |
| Lab | : 0 |
| ECTS | : 3 |
Students will make familiar with the basics of artificial neural networks methods and with their applicability to various problems including time series, regression, clustering, classification and dimension reduction.
Theory and application of regression, classification, time series and data reduction.
| 1. | Understand the concept and different types of artificial neural networks (ANN) |
| 2. | Learn the advantages and limitations of ANN |
| 3. | Appreciate the wide variety of applications of neural networks |
| 4. | Artificial neural network model to establish and interpret the output |
| 5. | Understand the complete process of using neural networks |
| Type of Assessment | Count | Percent |
|---|---|---|
| Attending Lectures | 1 | %5 |
| Assignment | 1 | %5 |
| Midterm Examination | 1 | %20 |
| Final Examination | 1 | %70 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 0 | 3 | 42 |
| Quiz | 2 | 1 | 1 | 4 |
| Midterm Examination | 1 | 10 | 1 | 11 |
| Final Examination | 1 | 15 | 1 | 16 |
| TOTAL WORKLOAD (hours) | 73 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | |
OÇ-1 | 4 | 4 | 4 | 4 | 3 | 3 | 2 |
OÇ-2 | 4 | 4 | 4 | 4 | 3 | 2 | 1 |
OÇ-3 | 4 | 4 | 4 | 4 | 2 | 4 | 4 |
OÇ-4 | |||||||
OÇ-5 | 4 | 4 | 4 | 4 | 4 | 4 | 5 |