GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
DATA WAREHOUSING AND DATA MINING/5201308
Course Title: DATA WAREHOUSING AND DATA MINING
Credits 3 ECTS 8
Semester 2 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Prof. Cevriye GENCER, PhD.
 -- WEB SITE(S) OF LECTURER(S)
  http://w3.gazi.edu.tr/~ctemel/index.html
 -- EMAIL(S) OF LECTURER(S)
  ctemel@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Know the definition of data mining.
Learn the phases of data mining.
Know data set generation.
Apprehend data cleaning and preprocessing.
Lay weight on data reduction.
Understand the data transformation process.
Learn modeling in data mining.
Know evaluation and research techniques.
Understand classification and clustering.
Discover the relationships.
 -- MODE OF DELIVERY
  The mode of the delivery of this course is video-conference virtual class.
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course.
 --COURSE CONTENT
1. Week  Introduction to Data Mining
2. Week  An Overview of Data Mining
3. Week  Phases of Data Mining
4. Week  Data Set Generation
5. Week  Data Cleaning
6. Week  Data Preprocessing
7. Week  Data Reduction
8. Week  Data Transformation
9. Week  Modeling in Data Mining
10. Week  Evaluation and Search Techniques
11. Week  Classification and Clustering
12. Week  Discovering the Relationships
13. Week  Practice
14. Week  Practice
15. Week  -
16. Week  -
 -- RECOMMENDED OR REQUIRED READING
  Data Mining Introductory and Advanced Topics, Margaret Dunham, ISBN: 0130888923, Prentice Hall, 2003.
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer, Demonstration, Drill - Practise
 -- WORK PLACEMENT(S)
  Project Presentations
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
30
 Assignment
0
0
 Exercises
0
0
 Projects
1
20
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
30
 Contribution of Final Examination to Overall Grade  
70
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
3
42
 Practising Hours of Course Per Week
0
 Reading
0
 Searching in Internet and Library
4
8
32
 Designing and Applying Materials
0
 Preparing Reports
4
10
40
 Preparing Presentation
1
20
20
 Presentation
1
10
10
 Mid-Term and Studying for Mid-Term
1
20
20
 Final and Studying for Final
1
30
30
 Other
0
 TOTAL WORKLOAD: 
194
 TOTAL WORKLOAD / 25: 
7.76
 ECTS: 
8
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Rule the information technologies and systems used in the units of the Business, have enough knowledge on the system management.X
2Master the information systems and technologies used in the units of the Business, design the system regarding the needs of the Business.X
3Make the related analyses for an information system and know all of the processes at the analysis, design and implementation stages of the database that belongs to the system.X
4Be able to follow current developments in modern business techniques and technologies; especially information technologies, gain know how.X
5Follow current affairs and convey information about trends systematically.X
6Be aware of the social transformation especially in their own field and social, legal and moral responsbilities belongs to other work field.
7Understand the disciplines and the interaction between his discipline and other relational ones, regard the disciplines and interactions in team works.X
8Develop their knowledge to the level of expertise which they obtained in license level.X
9Carry out a work which requires an expertness in this field.X
10Construct and perform an academic work in the field of Management Information Systems.X