COMPUTER ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | 1410002004 | ||||||||
Ders İsmi: | Artificial intelligence | ||||||||
Ders Yarıyılı: | Fall | ||||||||
Ders Kredileri: |
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Language of instruction: | TR | ||||||||
Ders Koşulu: | |||||||||
Ders İş Deneyimini Gerektiriyor mu?: | No | ||||||||
Type of course: | Bölüm Seçmeli | ||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||
Course Coordinator : | Dr.Öğr.Üyesi Recep DURANAY | ||||||||
Course Lecturer(s): | |||||||||
Course Assistants: |
Course Objectives: | The aim of the course is to provide students with information on basic techniques and methods in artificial intelligence and to enable students to have the ability to use artificial intelligence methods in solving practical problems. |
Course Content: | Basic concepts and methods of artificial intelligence. Problem solving using artificial intelligence; search methods using and not using problem information. Local search methods and simulated annealing algorithm. Meta-heuristic algorithms. Introduction to artificial neural networks. Game Problems. Prolog programming language, information representation and logical inference. |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | Basic Concepts, Artificial Intelligence history and philosophy | Course Book |
2) | Clever Agents | Course Book |
3) | Introduction to Problem Solving and Search Algorithms with Artificial Intelligence | Course Book |
4) | Search Algorithms That Don't Use Problem Information | Course Book |
5) | Intuitive Search | Course Book |
6) | Game Problems | Course Book |
7) | Meta-Heuristic Search Methods | Course Book |
8) | Midterm | |
9) | Artificial neural networks | Course Book |
10) | Knowledge-Based Agents | Course Book |
11) | First Order Logic | Course Book |
12) | Inference in First Order Logic | Course Book |
13) | Prolog Programming Language and Logical Programming | Course Book |
14) | Prolog Programming Language and Logical Programming | Course Book |
15) | Probabilistic Inference | Course Book |
16) | Final |
Course Notes / Textbooks: | Artificial Intelligence: A Modern Approach. Stuart Russell, Peter Norvig, Prentice Hall, Second Edition |
References: | Artificial Intelligence: A Modern Approach. Stuart Russell, Peter Norvig, Prentice Hall, Second Edition |
Ders Öğrenme Kazanımları | 1 |
2 |
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Program Outcomes | ||||||||||||||||
1) PO 1.1) Sufficient knowledge in mathematics, science and computer engineering | ||||||||||||||||
2) PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems. | ||||||||||||||||
3) PO 2.1) Identifying complex engineering problems | ||||||||||||||||
4) PO 2.2) Defining complex engineering problems | ||||||||||||||||
5) PO 2.3) Formulating complex engineering problems | ||||||||||||||||
6) PO 2.4) Ability to solve complex engineering problems | ||||||||||||||||
7) PO 2.5) Ability to choose and apply appropriate analysis and modeling methods | ||||||||||||||||
8) PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions. | ||||||||||||||||
9) PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product | ||||||||||||||||
10) PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications | ||||||||||||||||
11) PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications | ||||||||||||||||
12) PO 4.3) Ability to use information technologies effectively. | ||||||||||||||||
13) PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments | ||||||||||||||||
14) PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation | ||||||||||||||||
15) PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection | ||||||||||||||||
16) PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics | ||||||||||||||||
17) PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | PO 1.1) Sufficient knowledge in mathematics, science and computer engineering | |
2) | PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems. | |
3) | PO 2.1) Identifying complex engineering problems | |
4) | PO 2.2) Defining complex engineering problems | |
5) | PO 2.3) Formulating complex engineering problems | |
6) | PO 2.4) Ability to solve complex engineering problems | |
7) | PO 2.5) Ability to choose and apply appropriate analysis and modeling methods | |
8) | PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions. | |
9) | PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product | |
10) | PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications | |
11) | PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications | |
12) | PO 4.3) Ability to use information technologies effectively. | |
13) | PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments | 5 |
14) | PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation | |
15) | PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection | |
16) | PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics | |
17) | PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics |
Bireysel çalışma ve ödevi | |
Okuma |
Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama) | |
Homework |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | 10 | % 10 |
Homework Assignments | 5 | % 20 |
Midterms | 1 | % 30 |
Semester Final Exam | 1 | % 40 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 40 | |
total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Study Hours Out of Class | 14 | 7 | 98 |
Total Workload | 140 |