Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
8BLMS419Artificial Intelligence Applications3+0+03520.02.2026

 
Course Details
Language of Instruction Turkish
Level of Course Unit Bachelor's Degree
Department / Program Computer Engineering
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course To give general information about students with problems in Artificial Intelligence, the classic solution techniques to examine these problems, the solution approaches to solve problems that are difficult to discuss paratik or non-analytical solution.
Course Content Intelligent agent modeling of problerinin artificial intelligence approach, the search method of reaching a solution, well-informed ignorant nare solution methods, game problems, the first-grade mat, knowledge base creation, the principles of logical inference, to arrive at a decision under uncertainty, probability of reaching a decision based on natural language studies.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Dr. Arda Akdemir
Assistants Research Assist. Sinem Mizanalı
Work Placement(s) No

Recommended or Required Reading
Resources Russell S. and Norvig P, "Artificial Intelligence. A modern Approach", Prentice-hall, 2007.
Course Notes Lectures, Question-Answer, Project.
Assignments Bir grup projesi
Exams Vize ve Final Sınavları

Course Category
Mathematics and Basic Sciences %0
Engineering %10
Engineering Design %10
Social Sciences %0
Education %0
Science %0
Health %0
Field %80

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 30
Project 1 % 20
Final examination 1 % 50
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 3 42
Assignments 1 8 8
Mid-terms 1 2 2
Project 1 20 20
Final examination 1 2 2
Total Work Load   Number of ECTS Credits 5 116

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 explain the concepts of artificial intelligence, the intelligent agent approach, and basic problem-solving methods.
2 model and solve artificial intelligence problems using search, logical inference, and probabilistic decision-making methods.
3 develop data-driven artificial intelligence systems by applying machine learning and natural language processing approaches.
4 effectively apply artificial intelligence techniques to engineering problems and interpret the results.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Giriş. Zeki acenta yaklaşımı.
2 Search and problem analysis.
3 Knowledgeable problem-solving. Playing a game.
4 Agency up to the logical decision.
5 First-order logic method.
6 Creating a knowledge base. Logical systems to arrive at a decision.
7 Review.
8 Midterm exam.
9 Practical planning and behavior. Modeling uncertainty.
10 Probability in reaching a decision.
11 Simple and complex to arrive at a decision.
12 Machine learning approach.
13 Practical natural language relations.
14 Review.

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
C1 5
C2 5 4
C3 4 5
C4 4 5

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  https://obs.gedik.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=243268&curProgID=5607&lang=en