GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
ARTIFICIAL INTELLIGENCE/5231310
Course Title: ARTIFICIAL INTELLIGENCE
Credits 3 ECTS 8
Semester 2 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Assoc. Prof. Dr. Necmi ALTIN
 -- WEB SITE(S) OF LECTURER(S)
  http://websitem.gazi.edu.tr/site/naltin
 -- EMAIL(S) OF LECTURER(S)
  naltin@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Students will be expected to understand the usage of AI in the instructional applications
Definitions of AI,
Relations with the other scientific discyplines of AI,
Problems of AI,
Propositional logic,
Predicate logic,
Prolog programming,
Problems of AI and techniques used in the solution of these problems,
 -- MODE OF DELIVERY
  Distance Learning
 -- 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   Various definitions of AI.
2. Week  Relations with the other scientific discyplines of AI
3. Week  Components of a AI system
4. Week  Natural language processing
5. Week  Game modelling
6. Week  Knowledge modelling
7. Week  Pattern recognition
8. Week  Robotics
9. Week  Propositional logic-Basic concepts, conjunction and formulas
10. Week  Propositional logic-conjunction and formulas
11. Week  Predicate logic-predicate and function symbols
12. Week  Predicate logic-quantifiers
13. Week  Prolog and expert systems - 1
14. Week  Prolog and expert systems - 2
15. Week  
16. Week  
 -- RECOMMENDED OR REQUIRED READING
   Distance Learning Lecture Notes
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer, Demonstration, Drill - Practise
 -- WORK PLACEMENT(S)
  -
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
15
 Assignment
1
15
 Exercises
0
0
 Projects
0
0
 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
0
0
 Reading
10
5
50
 Searching in Internet and Library
8
6
48
 Designing and Applying Materials
5
6
30
 Preparing Reports
1
6
6
 Preparing Presentation
0
 Presentation
0
 Mid-Term and Studying for Mid-Term
1
6
6
 Final and Studying for Final
1
8
8
 Other
0
 TOTAL WORKLOAD: 
190
 TOTAL WORKLOAD / 25: 
7.6
 ECTS: 
8
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Improves and deepens the field knowledge at an expert level based on undergraduate proficiency.X
2Comprehends the interactions between the computer science and other related disciplines.X
3Uses expert level theoretical and practical knowledge acquired in the computer science field.X
4Creates new knowledge by integrating the computer science knowledge and the knowledge from related disciplines.X
5Defines a problem in the computer science field.X
6Analyses the problems in the computer science field by using scientific research methods.X
7Proposes solutions to the problems in the computer science field.X
8Solves problems in the computer science field.X
9Evaluates the results within perspectives of quality processes.X
10Develops new approaches and methods by taking responsibility in complex situations in the application stages.X