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FIRST CYCLE - BACHELOR'S DEGREE
FACULTY OF ENGINEERING
COMPUTER ENGINEERING DEPARTMENT
253 Computer Engineering
Course Information
Course Learning Outcomes
Course's Contribution To Program
ECTS Workload
Course Details
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COURSE INFORMATION
Course Code
Course Title
L+P Hour
Semester
ECTS
CENG 417
ARTIFICIAL INTELLIGENCE
3 + 0
7th Semester
5
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
1
Learning artificial intelligence concepts
2
Understanding the application areas
3
Enhancing the subject by studying on a sample project
COURSE'S CONTRIBUTION TO PROGRAM
PO 01
PO 02
PO 03
PO 04
PO 05
PO 06
PO 07
PO 08
PO 09
PO 10
PO 11
PO 12
LO 001
5
5
5
4
4
2
4
5
5
LO 002
5
5
5
3
4
1
4
4
4
LO 003
5
5
5
4
4
1
4
4
5
Sub Total
15
15
15
11
12
4
12
13
14
Contribution
5
5
5
4
4
1
4
0
0
4
5
0
ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities
Quantity
Duration (Hour)
Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)
14
2
28
Hours for off-the-classroom study (Pre-study, practice)
14
2
28
Assignments
5
4
20
Mid-terms
1
24
24
Final examination
1
30
30
Total Work Load
ECTS Credit of the Course
130
5
COURSE DETAILS
Select Year
All Years
2020-2021 Fall
2019-2020 Fall
2018-2019 Fall
2017-2018 Fall
2016-2017 Fall
2015-2016 Fall
2014-2015 Fall
2008-2009 Fall
Course Term
No
Instructors
Details
2020-2021 Fall
1
SEZAİ TOKAT
Details
2019-2020 Fall
3
SEZAİ TOKAT
Details
2018-2019 Fall
3
SEZAİ TOKAT
Details
2017-2018 Fall
5
SEZAİ TOKAT
Details
2016-2017 Fall
1
SEZAİ TOKAT
Details
2016-2017 Fall
1
EMRE ÇOMAK
Details
2015-2016 Fall
1
EMRE ÇOMAK
Details
2014-2015 Fall
3
EMRE 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
Weeks
Topics
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
Resources
Resources Language
Vasif Nabiyev, Yapay Zeka, 5. Baskı, Seçkin Yayınevi
Türkçe
Course Assessment
Assesment Methods
Percentage (%)
Assesment Methods Title
Final Exam
60
Final Exam
Midterm Exam
40
Midterm Exam
L+P:
Lecture and Practice
PQ:
Program Learning Outcomes
LO:
Course Learning Outcomes
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Home Page
About University
Name And Address
Acedemic Authorities
General Discription
Academic Calendar
General Admission Requirements
Recognition of Prior Learning
General Registration Procedures
ECTS Credit Allocation
Academic Guidance
Information For Students
Cost Of Living
Accommodation
Meals
Medical Facilities
Facilities for Special Needs Students
Insurance
Financial Support for Students
Student Affairs
Learning Facilities
International Programs
Language Courses
Internships
Sports Facilities and Leisure Activities
Student Associations
Practical Information for Mobile Students
Degree Programmes