Yazdır

Ders Tanımı

Ders Kodu Yarıyıl T+U Saat Kredi AKTS
INTRODUCTION TO DATA MINING ENM 424 8 3 + 0 3 5
Ön Koşul Dersleri
Önerilen Seçmeli Dersler
Dersin Dili Türkçe
Dersin Seviyesi Lisans
Dersin Türü SECMELI
Dersin Koordinatörü Dr.Öğr.Üyesi GÜLTEKİN ÇAĞIL
Dersi Verenler
Dersin Yardımcıları
Dersin Kategorisi
Dersin Amacı

1) Introducing Data Mining and Promoting Its Usage
2) To give ability to the students on analyzing large scale databases

Dersin İçeriği

This course covers the fundamentals of statistical, machine learning and database aspects of data mining . The course is composed of three parts. The first part will cover the fundamentals of statistics and machine learning approaches for data mining. In the second part, we will cover the fundamental data mining concepts and algorithms for tasks such as Online Analytical Processing (OLAP), association rules, clustering, etc. The final part of the course will focus on research areas such as text mining, collaborative filtering, link analysis and mining in biological domains (as time permits).

Dersin Öğrenme Çıktıları Öğretim Yöntemleri Ölçme Yöntemleri
1 - Utilizing classification algorithms 13 - 14 - 16 - A - C - D -
2 - Utilizing clustering algorithms 13 - 14 - 16 - A - C - D -
3 - Utilizing market basket analysis 13 - 14 - 16 - A - C - D -
4 - Ability of using data mining software 16 - D - F -
Öğretim Yöntemleri: 13:Lab / Workshop 14:Self Study 16:Project Based Learning
Ölçme Yöntemleri: A:Testing C:Homework D:Project / Design F:Performance Task

Ders Akışı

Hafta Konular ÖnHazırlık
1 Data Mining: An Introduction
2 Areas of interest in data mining
3 Introduction to Data Mining computer programs - Data Mining in Spreadsheet Programs
4 Prepering data to analysis (steps)
5 OLAP
6 Classification and Clustering
7 Decision tree
8 Statistics in data mining
9 Artificial intelligent in data mining
10 Neural Networks in data mining
11 Association rules
12 Other mining techniques in data mining- web and text mining
13 Sample applications
14 Data Mining Applications in Industry

Kaynaklar

Ders Notu

http://www.cagil.sakarya.edu.tr

lecture notes on this link

Ders Kaynakları

1. Gökhan Silahtaroğlu, Basic Data Mining with Concepts and Algorithms, Papatya Publications, (2008)
2. Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining, Addison Wesley, (2005).


Döküman Paylaşımı


Dersin Program Çıktılarına Katkısı

No Program Öğrenme Çıktıları KatkıDüzeyi
1 2 3 4 5
1 Engineering graduates with sufficient knowledge background on science and engineering subjects of their related area, and who are skillful in implementing theoretical and practical knowledge for modelling and solving engineering problems. X
2 Engineering graduates with skills in identifying, describing, formulating and solving complex engineering problems, and thus,deciding and implementing appropriate methods for analyzing and modelling. X
3 Engineering graduates with skills in designing a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; for this purpose, skills in implementing modern design methods. X
4 Engineering graduates with skills in developing, selecting and implementing modern techniques and tools required for engineering applications as well as with skills in using information technologies effectively. X
5 Engineering graduates with skills in designing and conducting experiments, collecting data, analyzing and interpreting the results in order to evaluate engineering problems. X
6 Engineering graduates who are able to work within a one discipline or multi-discipline team,as well as who are able to work individually X
7 Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology X
8 Engineering graduates with well-structured responsibilities in profession and ethics X
9 Engineering graduates having knowledge about practices in professional life such as project management, risk management and change management, and who are aware of innovation and sustainable development. X
10 Engineering graduates having knowledge about universal and social effects of engineering applications on health, environment and safety, as well as having awareness for juridical consequences of engineering solutions. X
11 Engineering graduates who are able to effectively communicate orally and officially in Turkish Language as well as who knows at least one foreign language

Değerlendirme Sistemi

YARIYIL İÇİ ÇALIŞMALARI SIRA KATKI YÜZDESİ
AraSinav 1 50
KisaSinav 1 15
Odev 1 10
KisaSinav 2 15
Odev 2 10
Toplam 100
Yıliçinin Başarıya Oranı 50
Finalin Başarıya Oranı 50
Toplam 100

AKTS - İş Yükü

Etkinlik Sayısı Süresi(Saat) Toplam İş yükü(Saat)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 2 32
Mid-terms 1 4 4
Assignment 2 10 20
Performance Task (Laboratory) 1 16 16
Toplam İş Yükü 120
Toplam İş Yükü /25(s) 4.8
Dersin AKTS Kredisi 4.8
; ;