| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Data Mining | BLM515 | Elective | Master's degree | 1 | Fall | 8 |
Name of Lecturer(s)
Prof. Dr. Yaşar BECERİKLİ
Prof. Dr. Nevcihan DURU
Associate Prof. Dr. Alev MUTLU
Learning Outcomes of the Course Unit
1) The students learn to apply data mining techniques
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
| Learning Outcomes | ||||||||||||
| 1 | No relation | No relation | High | Low | Low | Middle | High | High | Middle | Middle | Low | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
-Introduction -Data mining models -Classification -Association rules -Clustering
Weekly Schedule
1) introduction2) data preprocessing
3) clustering
4) classification
5) association rule mining
6) graph mining
7) multi relational data mining
8) inductive logic programming
9) location based social netwotk analysis
10) recommender systems
11) stream data mining
12) special topics in data mining
13) special topics in data mining
14) student presentations
15) student presentations
16) overview
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Language of Instruction
Turkish
Work Placement(s)
Not Required