GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
DATA MINING/İST4021
Course Title: DATA MINING
Credits 3 ECTS 4
Course Semester 7 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
To learn data mining algorithms.
Learning the statistical methods used in data mining.
To be able to learn data mining techniques with computer software.
To gain the ability to use what they learn in real application.

 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face and Lab application.
 --WEEKLY SCHEDULE
1. Week  Basic concepts
2. Week  Data base and data warehouse features
3. Week  Preparation and examining of data for analysis
4. Week  Decision Trees (ID3, C4.5, C5, CART, SLIQ, SPRINT)
5. Week  Decision Trees (Bayesian, Regression, CHAID)
6. Week  Decision Trees (k-nearest neighbor, minimum distance)
7. Week  Artificial neural networks
8. Week  Association Rules (AIS and SETM Algorithm), MIDTERM EXAM
9. Week  Association Rules (Apriori Algorithms)
10. Week  Clustering Analysis (Hierarchical Methods)
11. Week  Clustering Analysis (Partitioned Methods)
12. Week  Clustering Analysis (Density-based and grid-based algorithms)
13. Week  Genetic Algorithms
14. Week  Computer Applications
15. Week  FINAL EXAM
16. Week  -
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
30
 Assignment
1
5
 Application
1
5
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
5
2
10
 Searching in Internet and Library
5
3
15
 Material Design and Implementation
3
4
12
 Report Preparing
0
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
3
3
9
 Final Exam and Preperation for Final Exam
4
3
12
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
100
 TOTAL WORKLOAD / 25: 
4
 Course Credit (ECTS): 
4
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
11. The statistical textbooks which include latest information about statistics, equipment and other resources supported by scientific approach on undergraduate level have theoretical and practical knowledge.X
22. Statisticians by using knowledge and skills acquired at bachelor degree level model, analyze, and interpret datasets.X
33. Statisticians identify and analyze the problems with current developments in statistic and also develop solutions based upon researches and proofs.X
44. Statisticians apply theoretical and practical knowledge acquired in Statistics at bachelor degree level to the current problems.X
55. Statisticians have the ability to use computer software and computing technology at the certain level required by statistics field.X
66. Statisticians take responsibility at disciplinary and interdisciplinary studies as an individual or a team member.X
77. Statisticians must have knowledge and ability to follow development in the field of Statistics, and must develop life long-learning attitudes.X
88. By using a foreign language, statistician can keep track of every statistical information, and communicate with colleagues.X
99. Applying the statistical knowledge in the professional sense, statistician has social, scientific, and ethical values.X
1010. A statistician must have the ability to social sensitivity and socialization.X
1111. During the process of inference, a statistician uses time efficiently with the analytical thinking ability.X
 -- NAME OF LECTURER(S)
   (Prof.Dr. Bülent ALTUNKAYNAK)
 -- WEB SITE(S) OF LECTURER(S)
   (http://www.websitem.gazi.edu.tr/site/bulenta)
 -- EMAIL(S) OF LECTURER(S)
   (bulenta@gazi.edu.tr)