School/Faculty/Institute |
Faculty of Engineering |
Course Code |
COMP 450 |
Course Title in English |
Artificial Intelligence |
Course Title in Turkish |
Yapay Zeka |
Language of Instruction |
EN |
Type of Course |
Exercise,Flipped Classroom,Lecture |
Level of Course |
Introductory |
Semester |
Fall |
Contact Hours per Week |
Lecture: 2 |
Recitation: none |
Lab: 2 |
Other: none |
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Estimated Student Workload |
156 hours per semester |
Number of Credits |
6 ECTS |
Grading Mode |
Standard Letter Grade
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Pre-requisites |
None |
Expected Prior Knowledge |
Basic mathematics knowledge |
Co-requisites |
None |
Registration Restrictions |
Only Undergraduate Students |
Overall Educational Objective |
To learn the fundamental concepts of Artificial Intelligence and to become familiar with basic aspects of intelligent agents, knowledge representation, learning, and sensing. |
Course Description |
This course provides a comprehensive introduction to some fundamental aspects of Artificial Intelligence. The following topics are covered: Introduction, Intelligent agents, Search algorithms, A*search and heuristics, constraint satisfaction problems, Game trees, Knowldege representation, Learning: reinforcement learning, Decision trees, evolutionary methods, Artificial Neural Networks, Perceptrons, Deep Learning, Perception: Vision. |
Course Description in Turkish |
Bu derste; yapay zekanın temel kavramları şu konu başlıklar altında kapsamlı bir şekilde incelenmektedir: Akıllı etmenler, arama yöntemleri, A* arama ve sezgisel arama yötemleri, kısıt altında arama yöntemleri, oyun ağaçları, bilgi gösterimi, öğrenme, güdümlü öğrenme, karar ağaçları, evrimsel yöntemler, Yapay Sinir Ağları (YSA) , Perseptronlar ve Derin Öğrenme, Algılama:Yapay Görü. |
Course Learning Outcomes and Competences
Upon successful completion of the course, the learner is expected to be able to:
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Program Learning Outcomes/Course Learning Outcomes |
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1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
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2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors |
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3) An ability to communicate effectively with a range of audiences |
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4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts |
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5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives |
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6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
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7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. |
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Relation to Program Outcomes and Competences
N None |
S Supportive |
H Highly Related |
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Program Outcomes and Competences |
Level |
Assessed by |
1) |
An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
H |
Exam,Lab,Project
|
2) |
An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors |
N |
|
3) |
An ability to communicate effectively with a range of audiences |
S |
Lab,Project
|
4) |
An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts |
H |
Exam,Lab,Project
|
5) |
An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives |
S |
Project
|
6) |
An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
H |
Exam,Lab,Project
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7) |
An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. |
H |
Lab
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Prepared by and Date |
TUNA ÇAKAR , December 2018 |
Course Coordinator |
TUNA ÇAKAR |
Semester |
Fall |
Name of Instructor |
Dr. Öğr. Üyesi TUNA ÇAKAR |
Course Contents
Hafta |
Konu |
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Required/Recommended Readings | Artificial Intelligence: A Modern Approach (3rd Edition), Stuart Russell, Peter Norvig, Prentice Hall, 2010 |
Teaching Methods | Flipped classroom. Students work individually for assignments. |
Homework and Projects | Assignments & Project |
Laboratory Work | Application-based laboratory study
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Computer Use | Required |
Other Activities | none |
Assessment Methods |
Assessment Tools |
Count |
Weight |
Uygulama |
10 |
% 30 |
Küçük Sınavlar |
2 |
% 10 |
Ödev |
1 |
% 10 |
Projeler |
1 |
% 20 |
Final |
1 |
% 30 |
TOTAL |
% 100 |
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Course Administration |
cakart@mef.edu.tr
0 212 395 37 45
Instructor’s office: 5th floor
Office hours: After the lecture hours.
Rules for attendance: No attendance required.
Statement on plagiarism: YÖK Regulations
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