Ondokuz Mayıs Üniversitesi Bilgi Paketi - Ders Kataloğu

Description of Individual Course Units

Course Unit CodeCourse Unit TitleType of CourseYearSemesterECTS
END498 Artificial Intelligence / Specialized Systems (TE 8.3) 927001 4 8 6
Level of Course Unit
First Cycle
Objectives of the Course
Describing general structure of artificial intelligence and artificial intelligence’s algorithms, to teach artificial intelligence’s applications
Name of Lecturer(s)
Learning Outcomes
  1. To learn artificial intelligence methods and daily life practices
  2. To learn the necessary search paradigms for solving mathematical problems such as constraint problems and to apply them when necessary
  3. Understanding learning paradigms, practicing in everyday life and generating solutions to problems
Mode of Delivery
Formal Education
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
Language of Instruction
Turkish
Work Placement(s)
None
Course Contents
Basic concepts (search, problem solving, knowledge representation methods, planning, natural language processing), artificial neural networks, expert systems, genetic algorithms, fuzzy logic.
Weekly Detailed Course Contents
Week Theoretical Practice Laboratory
1.Entrance to artificial intelligence
2.Problem solving, natural language processing
3.Knowledge representation methods
4.Planning, search, vision, robotic, agent
5.Entrance to artificial neural networks
6.Artificial neural networks (Backpropagation)
7.Artificial neural networks (LVQ network)
8.Entrance to expert systems
9.Expert systems
10.Sample of expert system
11.Entrance to genetic algorithms
12.Sample of genetic algorithms
13.Entrance to fuzzy logic
14.Sample of fuzzy logic
15.
16.
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight (%)
Midterm Examination1100
SUM100
End Of Term (or Year) Learning ActivitiesQuantityWeight (%)
Final Examination1100
SUM100
Term (or Year) Learning Activities40
End Of Term (or Year) Learning Activities60
SUM100
Workload Calculation
ActivitiesQuantityTime(hours)Total Workload(hours)
Midterm Examination122
Final Examination122
Makeup Examination122
Attending Lectures13565
Homework51785
SUM156