| Language of Instruction |
Türkçe |
| Course Type |
Required Courses |
| Course Instructor(s) |
PROF. DR. ALPER TOLGA KUMTEPE |
| Mode of Delivery |
Face to face |
| Prerequisites |
Basic Mathematical Knowledge |
| Courses Recomended |
Basic Mathematical Knowledge |
| Recommended Reading List |
It will be announced later. |
| Assessment methods and criteria |
1 midterm exam, 1 final exam |
| Work Placement |
N/A |
| Catalog Content |
This course focuses on the process of transforming and preparing raw data into meaningful features that improve model performance. Students learn techniques for handling missing values, encoding categorical variables, scaling and normalizing data, and creating new features from existing ones. The course covers dimension reduction, feature selection methods, and automatic feature creation. Practical applications include hands-on exercises using large and complex datasets to improve predictive models in classification, regression, and clustering tasks, thereby developing analytical and modeling skills. |
Anadolu Info Package 
Turkish 
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