GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
HYBRID INTELLIGENT SYSTEMS/5091329
Course Title: HYBRID INTELLIGENT SYSTEMS
Credits 3 ECTS 7.5
Course Semester 1 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
Learning artificial neural networks
Learning fuzzy systems
Learning evolutionary algorithms
Learning hybrid artificial intelligence techniques

 -- MODE OF DELIVERY
  The mode of delivery of this course is face to face
 --WEEKLY SCHEDULE
1. Week  Fuzzy systems
2. Week  Evolutionary Algorithms
3. Week  Artificial neural networks
4. Week  Artificial neural networks - fuzzy systems
5. Week  Artificial neural networks - fuzzy systems
6. Week  Artificial neural networks - fuzzy systems
7. Week  Artificial neural networks - fuzzy systems
8. Week  Artificial neural networks - evolutionary algorithms
9. Week  Artificial neural networks - evolutionary algorithms
10. Week  Artificial neural networks - evolutionary algorithms
11. Week  Artificial neural networks - fuzzy systems - evolutionary algorithms
12. Week  Artificial neural networks - fuzzy systems - evolutionary algorithms
13. Week  Artificial neural networks - fuzzy systems - evolutionary algorithms
14. Week  Hybrid systems applications
15. Week  Hybrid systems applications
16. Week  Hybrid systems applications
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
20
 Assignment
6
20
 Application
0
0
 Projects
1
20
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
60
 Percentage of Final Exam to Total Score  
40
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
0
0
 Reading Tasks
14
1
14
 Searching in Internet and Library
14
1
14
 Material Design and Implementation
0
0
0
 Report Preparing
8
5
40
 Preparing a Presentation
2
8
16
 Presentation
2
1
2
 Midterm Exam and Preperation for Midterm Exam
1
22
22
 Final Exam and Preperation for Final Exam
1
38
38
 Other (should be emphasized)
0
0
0
 TOTAL WORKLOAD: 
188
 TOTAL WORKLOAD / 25: 
7.52
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1X
2X
3X
4X
5X
6X
7X
8X
9X
10X
11X
12X
 -- NAME OF LECTURER(S)
   (Prof. Dr. M. Ali Akcayol)
 -- WEB SITE(S) OF LECTURER(S)
   (http://w3.gazi.edu.tr/~akcayol/)
 -- EMAIL(S) OF LECTURER(S)
   (akcayol@gazi.edu.tr)