1. SHORT CYCLE - ASSOCIATE'S DEGREE
  2. DENİZLİ VOCATIONAL SCHOOL OF TECHNICAL SCIENCES
  3. COMPUTER TECHNOLOGY DEPARTMENT
  4. 331 COMPUTER PROGRAMMING
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
IBGL 224ARTIFICIAL INTELLIGENCE3 + 03rd Semester3

COURSE DESCRIPTION
Course Level Associate's Degree
Course Type Elective
Course Objective Designing and writing intelligence programs by using learning algoritm and structures
Course Content Discovering the learning algoritm and structures and writing the intelligence programs by using them
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Understanding the intelligence systems and be able to write intelligince software

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12PO 13PO 14
LO 001              
Sub Total              
Contribution00000000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)12224
Mid-terms144
Final examination188
Total Work Load

ECTS Credit of the Course





78

3
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Fall1İSMAİL SARI


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
IBGL 224 ARTIFICIAL INTELLIGENCE 3 + 0 1 Turkish 2023-2024 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Lecturer İSMAİL SARI ismailsari@pau.edu.tr DTMYO A0214 %
Goals Designing and writing intelligence programs by using learning algoritm and structures
Content Discovering the learning algoritm and structures and writing the intelligence programs by using them
Topics
WeeksTopics
1 Introduction to Artificial Intelligence and Intelligence Agents
2 Solving Problems by searching and Informed search
3 Solving Problems by searching and Informed search
4 Constraint Satisfaction and Adversarial Search
5 Constraint Satisfaction and Adversarial Search
6 Logical Agents
7 First Order Logic
8 Midterm
9 Inference in First Order Logic
10 Knowledge Representation
11 Quantifying Uncertainity
12 Probabilistic Reasoning
13 Learning From Examples and Decision Trees
14 Reinforcement Learning
Materials
Materials are not specified.
Resources
ResourcesResources Language
Yapay Zeka Algoritmaları ve Progamlama Dr.Ali Şir Attila Seçkin YayınlarıTürkçe
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam60Final Exam
Midterm Exam40Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes