Information
Code | BPP239 |
Name | Artificial intelligence |
Term | 2022-2023 Academic Year |
Semester | 3. 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 |
Label | E Elective |
Mode of study | Yüz Yüze Öğretim |
Catalog Information Coordinator | Öğr. Gör.Dr. YILMAZ KOÇAK |
Course Instructor |
Öğr. Gör.Dr. YILMAZ KOÇAK
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
To create a general culture on artificial intelligence concepts and techniques, to gain the knowledge and skills to analyze and write programs at the basic level with artificial neural networks, deep networks and other intelligent techniques.
Course Content
Definition of artificial intelligence, general structure of algorithms and systems, expert systems, artificial neural networks, deep networks and deep learning, optimization algorithms, logic and fuzzy logic, programming languages for artificial intelligence.
Course Precondition
No
Resources
Elmas, Ç, Applications of Artificial Intelligence, Seçkin Publisher, 2016, Ankara Karaboğa, D, Optimization Algorithms of Artificial Intelligence, Nobel Publisher, 2010, Kayseri Yılmaz, A, Artificial Intelligence, KODLAB, 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, Python in All Aspects, Kodlab, 2020
Notes
Artificial intelligence, Lecture Notes, Dr. Yılmaz KOÇAK
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 a selected programming language. |
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. | |
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 | Has basic knowledge of entrepreneurship. |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | Introduction to Artificial Intelligence | Review of Source Book | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
2 | Artificial Neural Networks and Basic Elements | Learning about artificial neural networks | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
3 | Creation of Artificial Neural Networks | Learning about artificial neural networks | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
4 | Structures of Artificial Neural Networks | Research about structures of artificial neural networks | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
5 | Supervised Learning | Research about learning methods | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
6 | Unsupervised Learning | Research about learning methods | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
7 | Deep Networks and Deep Learning | Research about deep learning | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
8 | Mid-Term Exam | Preparing for the exam | Ölçme Yöntemleri: Yazılı Sınav |
9 | Introduction to Fuzzy Logic | Research about fuzzy logic | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
10 | Crisp Sets and Fuzzy Sets | Learning about sets | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
11 | Genetic Algorithms | Learning about genetic algorithms | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
12 | Ant Colony Algorithms | Research about ant colony behavior | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
13 | Expert Systems | Research about expert systems | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
14 | Machine Learning | Research about machine learning | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
15 | Applications of Artificial Intelligence | Researching programming languages used in artificial intelligence applications | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma |
16 | Term Exams | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
17 | Term Exams | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
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 | 0 | 0 | 0 |
Mid-term Exams (Written, Oral, etc.) | 1 | 6 | 6 |
Final Exam | 1 | 16 | 16 |
Total Workload (Hour) | 78 | ||
Total Workload / 25 (h) | 3,12 | ||
ECTS | 3 ECTS |