GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
BAYESIAN NETWORKS AND ADAPTIVE HYPERMEDIA APPLICATIONS/4960221
Course Title: BAYESIAN NETWORKS AND ADAPTIVE HYPERMEDIA APPLICATIONS
Credits 3 ECTS 8
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
Explain basic concepts and principles of Bayesian networks.
Design an instructional adaptive hypermedia based on the Bayesain networks
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Fundamentals of the probability theory
2. Week  Fundamentals of the probability theory
3. Week  Fundamentals of the probability theory
4. Week  Fundamentals of the probability theory
5. Week  Introduction to the Bayesian networks
6. Week  Introduction to the Bayesian networks
7. Week  Introduction to the Bayesian networks
8. Week  Introduction to the Bayesian networks
9. Week  Introduction to the Bayesian networks
10. Week  Bayesian modelling techniques
11. Week  Bayesian modelling techniques
12. Week  Bayesian modelling techniques
13. Week  Adaptive hypermedia applications
14. Week  Adaptive hypermedia applications
15. Week  Adaptive hypermedia applications
16. Week  Adaptive hypermedia applications
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
0
0
 Assignment
0
0
 Application
0
0
 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
0
0
 Reading Tasks
12
3
36
 Searching in Internet and Library
8
2
16
 Material Design and Implementation
8
3
24
 Report Preparing
8
3
24
 Preparing a Presentation
6
2
12
 Presentation
1
1
1
 Midterm Exam and Preperation for Midterm Exam
6
2
12
 Final Exam and Preperation for Final Exam
12
2
24
 Other (should be emphasized)
0
0
0
 TOTAL WORKLOAD: 
191
 TOTAL WORKLOAD / 25: 
7.64
 Course Credit (ECTS): 
8
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1X
2X
3X
4X
5
6X
7
8X
9X
10
11
12
13
14
15
16
17
18
 -- NAME OF LECTURER(S)
   (Prof. Dr. Tolga GÜYER)
 -- WEB SITE(S) OF LECTURER(S)
   (www.tolgaguyer.com)
 -- EMAIL(S) OF LECTURER(S)
   (guyer@gazi.edu.tr)