Ders Bilgileri

#### Ders Tanımı

Ders Kodu Yarıyıl T+U Saat Kredi AKTS
DATA MINING BSM 619 0 3 + 0 3 6
 Dersin Dili Türkçe Dersin Seviyesi Doktora Dersin Türü SECMELI Dersin Koordinatörü Doç.Dr. NİLÜFER YURTAY Dersi Verenler Dersin Yardımcıları Dersin Kategorisi Dersin Amacı It is aimed to teach data mining technics and thier applications in this course Dersin İçeriği Introduction to data minig, their definitions, backrground, operations, algorithms. Data mining applications and problems. Text minig, web mining. Examples.
 Dersin Öğrenme Çıktıları Öğretim Yöntemleri Ölçme Yöntemleri 1 - Expose relations in data heaps automatically. 1 - 2 - 4 - 8 - A - C - D -
 Öğretim Yöntemleri: 1:Lecture 2:Question-Answer 4:Drilland Practice 8:Group Study Ölçme Yöntemleri: A:Testing C:Homework D:Project / Design

#### Ders Akışı

Hafta Konular ÖnHazırlık
1 General definitions
2 Data warehouses and OLAP
3 Data mining models
4 Classification -decision trees, Classification statistic algorithms
5 Classification distance algorithms, artificial neural networks
6 Association rules and relation analysis
7 Clustering- hierarchical methods
8 Partitioning methods, Density based algorithms
9 Grid based algorithms
10 Data mining in servis sector
11 Data mining in health sector
12 Data mining in production sector
13 Web mining
14 Data mining in education sector

#### Kaynaklar

Ders Notu http://nyurtay.sakarya.edu.tr
Ders Kaynakları Silahtaroğlu,G., Veri Madenciliği, Papatya Yayınevi,2008

#### Dersin Program Çıktılarına Katkısı

No Program Öğrenme Çıktıları KatkıDüzeyi
1 2 3 4 5
1 ability to complete and implement “limited or incomplete data” by using the scientific methods. X
2 ability to consolidate engineering problems, develop proper method(s) to solve and apply the innovative solutions to them X
3 ability to develop new and original ideas and method(s), to develop new innovative solutions at design of system, component or process X
4 gain comprehensive information on modern techniques, methods and their borders which are being applied to engineering X
5 ability to design and apply analytical, modelling and experimental based research, analyze and interpret the faced complex issues during the design and apply process X
6 gain high level ability to define the required information and data X
7 ability to work in multi-disciplinary teams and to take responsibility to define approaches for complex situations X
8 systematic and clear verbal or written transfer of the process and results of studies at national and international environments X
9 aware of social, scientific and ethical values guarding adequacy at all professional activities and at the stage of data collection, interpretation and announcement X
10 aware of new and developing application of profession and ability to analyze and study on those applications X
11 ability to interpret engineering application’s social and environmental dimensions and it’s compliance with the social environment X

#### Değerlendirme Sistemi

YARIYIL İÇİ ÇALIŞMALARI SIRA KATKI YÜZDESİ
AraSinav 1 50
KisaSinav 1 10
Odev 1 30
KisaSinav 2 10
Toplam 100
Yıliçinin Başarıya Oranı 50
Finalin Başarıya Oranı 50
Toplam 100

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