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Information
| Code | BL237 |
| Name | Artificial Intelligence Applications |
| Term | 2024-2025 Academic Year |
| Semester | 3. Semester |
| Duration (T+A) | 2-1 (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 | Mahir ATMIŞ |
| Course Instructor |
1 2 |
Course Goal / Objective
To test the machine learning methods used in our age on current data.
Course Content
"Introduction and definitions, classification/regression problem, supervised learning, inear regression, the smallest squares of error, logistics regression, perceptron, bias-variance, feature selection, artificial neural networks, decision trees, support vector machines, unsupervised learning"
Course Precondition
None
Resources
Lecture Notes Mahir Atmış
Notes
Uygulamalar ile Python ve Yapay Zeka, Emrah Aydemir
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explains the concept of Artificial Intelligence and algorithms. |
| LO02 | Explains the concept of Artificial Neural Networks and deep networks. |
| LO03 | Teachs the concepts of supervision and unsupervised learning. |
| LO04 | Teaches the concepts of clustering. |
| LO05 | Tests learning algorithms on ready data sets. |
| LO06 | Understands the basic logic of learning algorithms. |
| LO07 | Uses state of the art learning algorithms. |
| LO08 | Develops their own learning algorithm. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Has basic knowledge, current technologies, and applied skills. | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Gains knowledge about occupational health and safety, environmental awareness, and quality processes. | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Has knowledge of basic electronic components comprising computer hardware and their operations. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Has knowledge about Atatürk's Principles and History of Revolution. | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Keeps track of current developments and applications in computer programming, and utilizes them effectively. | 4 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Has the ability to solve problems in the field of computer programming. | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Creates algorithms and data structures, and performs mathematical calculations. | 5 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Explains and implements web programming technologies. | |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Performs database design and management. | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Tests software and resolves errors. | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Can utilize software and package programs in the field of computer programming. | 4 |
| PLO12 | Beceriler - Bilişsel, Uygulamalı | Explains, designs and installs network systems. | |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | uses word processor, spreadsheet, presentation programs. | |
| PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Can effectively present thoughts on computer technologies through written and verbal communication, expressing them clearly and comprehensibly. | |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Takes responsibility as a team member to solve unforeseen complex problems encountered in practical applications of computer programming. | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Has awareness in career management and lifelong learning. | |
| PLO17 | Yetkinlikler - Alana Özgü Yetkinlik | Has societal, scientific, cultural, and ethical values in the collection, application, and announcement of results related to computer technologies. | |
| PLO18 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Follows developments in the field using a foreign language and communicates with colleagues. | |
| PLO19 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Can effectively communicate in Turkish both in written and oral forms. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | What's Learning? | Preparation is not required. | Öğretim Yöntemleri: Anlatım |
| 2 | Clustering algorithms | Preparation is not required. | Öğretim Yöntemleri: Anlatım |
| 3 | Classification algorithms | Preparation is not required. | Öğretim Yöntemleri: Anlatım |
| 4 | Regression | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 5 | Decision Trees | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 6 | Support Vector Machines | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 7 | Bayes Classification | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Yazılı Sınav |
|
| 9 | Artificial Neural Networks | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 10 | Artificial Neural Networks (continuation) | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 11 | Convolutional Neural Networks | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 12 | Convolutional Neural Networks (continuation) | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 13 | Reinforcement Learning | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 14 | Unsupervised Learning | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 15 | Unsupervised Learning (continuation) | Preparation is not required. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 16 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav |
|
| 17 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 2 | 28 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 2 | 2 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 5 | 5 |
| Final Exam | 1 | 10 | 10 |
| Total Workload (Hour) | 87 | ||
| Total Workload / 25 (h) | 3,48 | ||
| ECTS | 3 ECTS | ||