Information Systems Engineering | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | FET308 | ||||||||
Ders İsmi: | Data Mining | ||||||||
Ders Yarıyılı: | Spring | ||||||||
Ders Kredileri: |
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Language of instruction: | Turkish | ||||||||
Ders Koşulu: | |||||||||
Ders İş Deneyimini Gerektiriyor mu?: | No | ||||||||
Type of course: | Bölüm Seçmeli | ||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||
Course Coordinator : | Asst. Prof. Dr. SAJJAD NEMATZADEH MİANDOAB | ||||||||
Course Lecturer(s): |
Asst. Prof. Dr. SAJJAD NEMATZADEH MİANDOAB |
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Course Assistants: |
Course Objectives: | This course aims to explain the basic concepts of data mining to students in an applied way. |
Course Content: | The course covers data science fundamentals, programming with python, data preparation, descriptive methods and predictive methods. |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | Fundamentals of Data Mining | |
2) | Data and Data Science Concepts | |
3) | Data Discovery | |
4) | Python Programming | |
5) | Data Editing with Python | |
6) | Predictive Methods | |
7) | Decision Trees | |
8) | Midterm | |
9) | Classification and Regression | |
10) | Machine Learning | |
11) | Descriptive Methods | |
12) | Clustering | |
13) | Association Rules | |
14) | Project Presentations | |
15) | Final Exam |
Course Notes / Textbooks: | TAN, Pang-Ning; STEINBACH, Michael, KUMAR, Vipin, Introduction to data mining. Pearson Education India, 2016. |
References: | AGGARWAL, Charu C. Data mining: the textbook. Springer, 2015. |
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