GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
APPLIED ARTIFICIAL INTELLIGENCE/5021329
Course Title: APPLIED ARTIFICIAL INTELLIGENCE
Credits 3 ECTS 7.5
Semester 1 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Prof. Dr. Seref SAGIROGLU
 -- WEB SITE(S) OF LECTURER(S)
  ceng.gazi.edu.tr/~ss
 -- EMAIL(S) OF LECTURER(S)
  ss@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Students learn Artificial Intelligence techniques theoretically and practically.
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 -- PREREQUISITES AND CO-REQUISITES
  None
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course.
 --COURSE CONTENT
1. Week  General introduction
2. Week  Intelligence, Artificial Intelligence, Artificial Intelligence techniques and basic principles
3. Week  Learning strategies
4. Week  Learning strategies
5. Week  Problem solving and searching strategies
6. Week  Principles
7. Week  Artificial Intelligence Tools
8. Week  Artificial Intelligence Tools
9. Week  Artificial Intelligence Tools
10. Week  Knowledge representation, methods and techniques
11. Week  Knowledge representation, methods and techniques
12. Week  Problem-solving methods
13. Week  Application examples of LISP and PROLOG
14. Week  Projects presentation
15. Week  
16. Week  
 -- RECOMMENDED OR REQUIRED READING
  Mühendislikte Yapay Zeka Kullanımı I: Yapay Sinir Ağları, Ufuk Kitabevi, 2003.
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer, Demonstration, Drill - Practise
 -- WORK PLACEMENT(S)
  None
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
0
30
 Assignment
0
10
 Exercises
0
0
 Projects
0
60
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
40
 Contribution of Final Examination to Overall Grade  
60
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
13
3
39
 Practising Hours of Course Per Week
2
3
6
 Reading
14
3
42
 Searching in Internet and Library
16
2
32
 Designing and Applying Materials
5
5
25
 Preparing Reports
7
3
21
 Preparing Presentation
2
5
10
 Presentation
2
5
10
 Mid-Term and Studying for Mid-Term
1
5
5
 Final and Studying for Final
1
10
10
 Other
0
 TOTAL WORKLOAD: 
200
 TOTAL WORKLOAD / 25: 
8
 ECTS: 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Can improve his computer engineering knowledgeX
2Can acknowledge the multidiciplinary aspects of computer engineeringX
3Can use his computer engineering knowledgeX
4Can acknowledge the multidiciplinary aspects of computer engineeringX
5Can use his computer engineering knowledge to solve problemsX
6Can define computer engineering problemsX
7Can propose solutions to computer engineering problemsX
8Can solve computer engineering problemsX
9Can evaluate solutions using qualtiy metricsX
10Can come up with new approaches to application problemsX