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Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
---|---|---|---|---|---|---|
Data Mining | MEN415 | Elective | Bachelor's degree | 4 | Fall | 5 |
Associate Prof. Dr. Burcu ÖZCAN TÜRKKAN
Assistant Prof. Dr. Mehlika KOCABAŞ AKAY
1) Students can choose which method is more appropriate on a given data set by comparing the results of different algorithms.
2) Students can analyze data mining problems, the data mining tasks can be performed independently.
3) Students can read scientific papers on data mining, can interpret.
4) Students can remove the pattern by using a variety of algorithms .
Program Competencies | ||||||||||||
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
Learning Outcomes | ||||||||||||
1 | No relation | Low | Low | No relation | No relation | No relation | No relation | No relation | Middle | No relation | No relation | |
2 | No relation | Low | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
3 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | Low | No relation | |
4 | No relation | Low | No relation | No relation | Middle | No relation | No relation | No relation | No relation | No relation | No relation |
Face to Face
None
Not Required
This course includes applied scientific research writing, defining large datasets, evaluating a research problem, research questions and their implications, collecting and preparing real-world data, data analysis methods, choosing an analysis method, data analysis, solving the problem. At the end of the course, an empirical research report will be prepared and presented using modern data mining methods.
Turkish
Not Required