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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
CENG 417ARTIFICIAL INTELLIGENCE3 + 07th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective This subject aims to give students an introduction to the field of Artificial Intelligence, covering the basic techniques and mechanisms for AI programming. The students completing this subject will have understanding of the historical and conceptual development of AI, the goals of AI and the methods employed to achieve them, the social and economic roles of AI and also have the skills to analyze problems and determine where AI techniques are applicable, implement AI problem-solving techniques.
Course Content Introduction to artificial intelligence, Natural and Artificial Intelligence, Turing Test, Searching Methods, Planning, Heuristic Problem Solving, Knowledge representation, Predicate Logic, AI programming languages, Programming in Common Lisp, Game Theory, Genetic Algorithms, Expert Systems, Artificial Intelligence Applications.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Learning artificial intelligence concepts
2Understanding the application areas
3Enhancing the subject by studying on a sample project

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 0015554424  55 
LO 0025553414  44 
LO 0035554414  45 
Sub Total1515151112412  1314 
Contribution555441400450

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14228
Hours for off-the-classroom study (Pre-study, practice)14228
Assignments5420
Mid-terms12424
Final examination13030
Total Work Load

ECTS Credit of the Course






130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2020-2021 Fall1SEZAİ TOKAT
Details 2019-2020 Fall3SEZAİ TOKAT
Details 2018-2019 Fall3SEZAİ TOKAT
Details 2017-2018 Fall5SEZAİ TOKAT
Details 2016-2017 Fall1SEZAİ TOKAT
Details 2016-2017 Fall1EMRE ÇOMAK
Details 2015-2016 Fall1EMRE ÇOMAK
Details 2014-2015 Fall3EMRE ÇOMAK


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
CENG 417 ARTIFICIAL INTELLIGENCE 3 + 0 1 Turkish 2020-2021 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Prof. Dr. SEZAİ TOKAT stokat@pau.edu.tr MUH A0226 MUH A0254 %
Goals This subject aims to give students an introduction to the field of Artificial Intelligence, covering the basic techniques and mechanisms for AI programming. The students completing this subject will have understanding of the historical and conceptual development of AI, the goals of AI and the methods employed to achieve them, the social and economic roles of AI and also have the skills to analyze problems and determine where AI techniques are applicable, implement AI problem-solving techniques.
Content Introduction to artificial intelligence, Natural and Artificial Intelligence, Turing Test, Searching Methods, Planning, Heuristic Problem Solving, Knowledge representation, Predicate Logic, AI programming languages, Programming in Common Lisp, Game Theory, Genetic Algorithms, Expert Systems, Artificial Intelligence Applications.
Topics
WeeksTopics
1 Definition, different perspectives, historical development, application areas of Artificial Intellgence
2 Knowledge Representation
3 Heuristics ans Heuristics based Search Algortihms
4 Game Theory, Game Tree
5 Genetic Algorithms
6 Fuzzy Logic
7 Logical Programming
8 Midterm
9 Student Presentations
10 Student Presentations
11 Student Presentations
12 Student Presentations
13 Student Presentations
14 Student Presentations
Materials
Materials are not specified.
Resources
ResourcesResources Language
Vasif Nabiyev, Yapay Zeka, 5. Baskı, Seçkin YayıneviTürkçe
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