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Information
| Code | BPP266 |
| Name | Artificial Intelligence |
| Term | 2024-2025 Academic Year |
| Semester | 4. Semester |
| Duration (T+A) | 2-0 (T-A) (17 Week) |
| ECTS | 3 ECTS |
| National Credit | 2 National Credit |
| Teaching Language | Türkçe |
| Level | Ön Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Öğr. Gör.Dr. YILMAZ KOÇAK |
| Course Instructor |
1 |
Course Goal / Objective
To learn definition and methods of artificial intelligence, to learn general structure of intelligent algorithms, to have knowledge about artificial neural networks, deep learning, expert systems, fuzzy logic techniques. To prepare basic artificial intelligence applications with artificial intelligence programs (Python, Matlab, etc.).
Course Content
Definition of artificial intelligence, algorithms and general structure of systems, artificial neural networks, deep networks and deep learning, crips logic and fuzzy logic, software tools using artificial intelligence.
Course Precondition
Yok
Resources
Yapay Zeka Ders Notları, Dr. Yılmaz KOÇAK
Notes
Elmas, Ç, Yapay Zeka Uygulamaları, Seçkin Yayınevi, Mart 2016, Ankara Karaboğa, D, Yapay Zeka Optimizasyon Algoritmaları, Nobel Yayınevi, Ocak 2010, Kayseri Yılmaz, A, Yapay Zeka, KODLAB, Kasım 2017, İstanbul Manaswi NK, Deep Learning with Applications Using Python, Apress, 2018 India Wirsansky E, Hands On Genetics Algorithms with Python, Packt, 2020, Birmingham Özgül, F, Her Yönüyle Python, Kodlab, 2020
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explains artificial intelligence concept and algorithms |
| LO02 | Explains articial neural networks and deep networks |
| LO03 | Expresses fuzzy sets and fuzzy logic |
| LO04 | Expresses artificial intelligence optimization algorithms such as genetic algorihtms, colony concepts |
| LO05 | Prepares basics program using programing languages used artificial intelligence (Python, Matlab etc.) |
| LO06 | Applies artificial intelligence algorithms using programming languages |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Communicates effectively with all partners on a sectoral basis. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | has the basic knowledge necessary to develop computer software, to establish algorithm, sequential and simultaneous flow logic | 3 |
| PLO03 | Yetkinlikler - Alana Özgü Yetkinlik | Designs systems for fundamental problems in microcontrollers, embedded systems and analog/digital electronics. | 1 |
| PLO04 | Yetkinlikler - Alana Özgü Yetkinlik | Uses basic software related to information and communication technologies, specific to his profession. | 2 |
| PLO05 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Applies the software and hardware developments in the field of Computer Programming independently. | 3 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Explains the necessary methods for solving well-defined problems in the field of Computer Technologies and Programming. | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Has the basic knowledge level required to develop software specific to web, mobile and other electronic platforms. | 3 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Develops software for desktop and other environments. | 3 |
| PLO09 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Takes an active role in project development processes, independently or as part of a group, within a planned project. | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Knows project planning, development and implementation processes. | |
| PLO11 | Yetkinlikler - Alana Özgü Yetkinlik | Performs data storage, editing, querying, etc. operations in computer and network environment. | |
| PLO12 | Yetkinlikler - Alana Özgü Yetkinlik | It has the ability to solve unpredictable hardware and software problems. | |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | Codes software components that have been analyzed and the algorithm has been prepared. | 4 |
| PLO14 | Bilgi - Kuramsal, Olgusal | Knows the methods to be used in software development. | 4 |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Constantly follows current innovations and developments in the field of information technologies. | 2 |
| PLO16 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Communicates verbally and in writing in a foreign language. | |
| PLO17 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | It has the phenomenon of the necessity of moral and ethical behaviors related to the information technology profession. | |
| PLO18 | Yetkinlikler - Alana Özgü Yetkinlik | Has the necessary awareness of occupational safety in her field. | |
| PLO19 | Beceriler - Bilişsel, Uygulamalı | It uses operating systems with administrative features. | |
| PLO20 | Bilgi - Kuramsal, Olgusal | Have basic knowledge about entrepreneurship, career management and lifelong learning. | |
| PLO21 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Has environmental awareness, environmental sensitivity, basic knowledge about waste storage and safety. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Artificial Intelligence | Examination of source books | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 2 | Artificial Neural Networks and Basic Elements | Learning about artificial neural networks | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 3 | Creation of Artificial Neural Networks | Learning about artificial neural networks | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 4 | Structures of Artificial Neural Networks | Researching the structures of artificial neural networks | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 5 | Supervised Learning | Researching learning methods | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 6 | Unsupervised Learning | Researching learning methods | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 7 | Deep Networks and Deep Learning | Exploring the concept of deep learning | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 8 | Mid-Term Exam | exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Introduction to Fuzzy Logic | Researching the concept of fuzzy logic | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 10 | Crisp Sets and Fuzzy Sets | Learning the concept of sets | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 11 | Genetic Algorithms | Research genetic algorithm concept | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 12 | Application Areas of Genetic Algorithms | Researching areas where genetic algorithms are used | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 13 | Ant Colony Algorithms | Researching ant colony behavior | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 14 | Application Fields of Ant Colony Algorithms | Researching areas where ant colony algorithm is used | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 15 | Applications of Artificial Intelligence | Researching programming languages used in artificial intelligence applications | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 16 | Term Exams | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 2 | 28 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 2 | 28 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 10 | 10 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 8 | 8 |
| Final Exam | 1 | 12 | 12 |
| Total Workload (Hour) | 86 | ||
| Total Workload / 25 (h) | 3,44 | ||
| ECTS | 3 ECTS | ||