Data Analysis and Management
Engineering Management (Non Thesis) (EP)
Institute of Natural and Applied Sciences
Second Cycle (Master's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Data Analysis and Management | MHY131 | Elective | Master's degree | 1 | Fall | 6 |
Name of Lecturer(s)
Prof. Dr. Gülşen AKMAN
Associate Prof. Dr. Burcu ÖZCAN TÜRKKAN
Learning Outcomes of the Course Unit
1) It reveals the relationships in large data stack.
2) Apply data mining models to problems.
3) To interpret and understand the data set which will use the data mining method
Program Competencies-Learning Outcomes Relation
Bölümün/programın program yeterlilikleri sistemde olmadığından ilişkilendirme işlemi yapılamamıştır.
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
Experimental design, classification, data analysis makes learning the clustering and association rules.
Weekly Schedule
1) Basic concepts2) Data pre-processing
3) Data Conversion
4) Analysis of the experimental data
5) Computer Analysis
6) Data Mining
7) Data Mining Methods
8) Mid Term Examination
9) Classification and Application with ID3 Algorithm ( industrial applications )
10) Classification with Decision Trees
11) Memory -Based Classification ( k- nearest neighbor algorithm and weighted voting algorithms)
12) Hierarchical Clustering Methods unifying Distance Criteria
13) Non- Hierarchical Clustering - K Average Method
14) Association Rules Apriori Algorithm Basket Analysis
15) Homework
16) Final Examination
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Language of Instruction
Turkish
Work Placement(s)
Not Required