Data Mining
Description
All our operations with devices such as computer, tablet and smartphone produce
data and leave traces about us. A correct analysis and evaluation of these traces
reveal patterns and information. Data mining is a method used for this purpose.
Using data mining, a company can determine its possible customers, a doctor can
diagnose various diseases based on symptoms, or digital fraud can be detected.
This course is a point of departure for those who are interested in data mining.
There are no prerequisites to take the course. This four-week course that requires
one hour of contact per week is mainly based on individual learning. Participants
need to complete a series of activities individually every week. The course
instructor will be following participants, and intervene in the activities when
required. Participants can contact the instructor for any questions related to the
course.
data and leave traces about us. A correct analysis and evaluation of these traces
reveal patterns and information. Data mining is a method used for this purpose.
Using data mining, a company can determine its possible customers, a doctor can
diagnose various diseases based on symptoms, or digital fraud can be detected.
This course is a point of departure for those who are interested in data mining.
There are no prerequisites to take the course. This four-week course that requires
one hour of contact per week is mainly based on individual learning. Participants
need to complete a series of activities individually every week. The course
instructor will be following participants, and intervene in the activities when
required. Participants can contact the instructor for any questions related to the
course.
Course format
Guided Course
Prerequisites
You should be able to understand Turkish
Information
| Language |
Turkish |
 Self-paced
|
Yes |
| Hours of study | 25 hours |
| EQF-Level | EQF level 5 - Foundation/Diploma of Higher Education |
 Rights
|
Open license: (re-)use it |
 Requirements
|
Free admittance |
 Cost
|
Free of charge |
 Delivery mode
|
Learn anywhere online |
 QA
|
Quality assured |
| Massive | Massive |
| Full Course Experience | Full course experience |
| Provider | OpenupEd |
07-Nov-2016
Data Mining
http://akadema.anadolu.edu.tr/course-veri-madenciligi.php
All our operations with devices such as computer, tablet and smartphone produce
data and leave traces about us. A correct analysis and evaluation of these traces
reveal patterns and information. Data mining is a method used for this purpose.
Using data mining, a company can determine its possible customers, a doctor can
diagnose various diseases based on symptoms, or digital fraud can be detected.
This course is a point of departure for those who are interested in data mining.
There are no prerequisites to take the course. This four-week course that requires
one hour of contact per week is mainly based on individual learning. Participants
need to complete a series of activities individually every week. The course
instructor will be following participants, and intervene in the activities when
required. Participants can contact the instructor for any questions related to the
course.
data and leave traces about us. A correct analysis and evaluation of these traces
reveal patterns and information. Data mining is a method used for this purpose.
Using data mining, a company can determine its possible customers, a doctor can
diagnose various diseases based on symptoms, or digital fraud can be detected.
This course is a point of departure for those who are interested in data mining.
There are no prerequisites to take the course. This four-week course that requires
one hour of contact per week is mainly based on individual learning. Participants
need to complete a series of activities individually every week. The course
instructor will be following participants, and intervene in the activities when
required. Participants can contact the instructor for any questions related to the
course.
Turkish
Self-paced
0
25
Anadolu University
http://akadema.anadolu.edu.tr/
[{"file":"\/images\/institution_logos\/Anadolu2.png","params":"{\"rotation\":0,\"scale\":100,\"imagedim\":{\"x\":200,\"y\":200,\"w\":200,\"h\":100},\"cropdim\":{\"x\":200,\"y\":200,\"w\":200,\"h\":100},\"crop\":true,\"mainimagedim\":{\"x\":200,\"y\":200,\"w\":200,\"h\":100}}"}]
Guided Course
You should be able to understand Turkish
For more information about the EFQ levels click here
EQF level 5 - Foundation/Diploma of Higher Education
Emrah Emre ÖZKESKİN
1. Select an image to upload (add files)
2. Click 'start upload'
3. Set the crop settings by clicking on four arrows icon.
4. Drag the crop area and zoom or rotate the image if needed.
2. Click 'start upload'
3. Set the crop settings by clicking on four arrows icon.
4. Drag the crop area and zoom or rotate the image if needed.
Always online
Massive
Full Course Experience
OpenupEd
- 0
Anadolu University
2016-12-06 14:13:49
Türkçe
Veri Madenciliği
Bilgisayarlar, tabletler ya da akıllı telefonlar gibi cihazlardaki bütün eylemlerimiz veri üretir ve bize dair bir iz bırakır. Eğer bu izler doğru analiz edilir ve değerlendirilirse desen ve bilgiler açığa çıkartılabilir. Veri madenciliği bu amaçla kullanılan bir yöntemdir. Veri madenciliğini kullanarak bir firma olası müşterilerini belirleyebilir; bir doktor semptomlardan farklı hastalıkları tanılayabilir ya da dijital dolandırıcılıklar tespit edilebilir. Veri madenciliğine giriş olarak adlandırdığımız bu dersimiz bu konulara merak duyan kişilere bir başlangıç noktası olmayı hedeflemektedir.
Bu derse katılmak için önşart yoktur. Veri madenciliğini merak eden herkes için başlangıç aşaması olarak tasarlanan bu ders, haftalık bir saat, toplam 4 hafta zaman alacak şekilde tasarlanmıştır. Ders büyük ölçüde bireysel öğrenmeye dayalı geliştirilmiştir. Her hafta bir dizi etkinliği bireysel olarak tamamlamanız beklenmektedir ancak dersin öğretim elemanı sürekli olarak sizleri izleyecek ve gerekli durumlarda uyarılarda bulunacaktır. Ayrıca ihtiyaç duyduğunuzda ders ile ilgili sorularınızı, dersin öğretim elemanlarına sorabilirsiniz.
Bu derse katılmak için önşart yoktur. Veri madenciliğini merak eden herkes için başlangıç aşaması olarak tasarlanan bu ders, haftalık bir saat, toplam 4 hafta zaman alacak şekilde tasarlanmıştır. Ders büyük ölçüde bireysel öğrenmeye dayalı geliştirilmiştir. Her hafta bir dizi etkinliği bireysel olarak tamamlamanız beklenmektedir ancak dersin öğretim elemanı sürekli olarak sizleri izleyecek ve gerekli durumlarda uyarılarda bulunacaktır. Ayrıca ihtiyaç duyduğunuzda ders ile ilgili sorularınızı, dersin öğretim elemanlarına sorabilirsiniz.
Rehber Gözetimli
