Information
Unit | FACULTY OF ARCHITECTURE |
INTERIOR ARCHITECTURE PR. | |
Code | IMS311 |
Name | AI-Assisted Design |
Term | 2025-2026 Academic Year |
Semester | 5. Semester |
Duration (T+A) | 2-0 (T-A) (17 Week) |
ECTS | 3 ECTS |
National Credit | 2 National Credit |
Teaching Language | Türkçe |
Level | Belirsiz |
Type | Normal |
Label | E Elective |
Mode of study | Yüz Yüze Öğretim |
Catalog Information Coordinator | Arş. Gör. Emre PINAR |
Course Instructor |
The current term course schedule has not been prepared yet.
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Course Goal / Objective
This course aims to teach interior architecture students the basic principles of artificial intelligence technologies and to provide them with the skills to integrate these technologies into their design processes. By focusing on topics such as data analysis, AI-assisted design, visualization and decision support systems, students are expected to effectively use innovative digital design tools.
Course Content
Focuses on the applications of artificial intelligence technologies in interior design processes. Within the scope of the content; the history of artificial intelligence, basic concepts, data science, prompt engineering, design and visualization tools supported by artificial intelligence, design optimization supported by artificial intelligence and the relationship between artificial intelligence and sustainability are examined. In addition, students develop hands-on skills in developing projects/designs, analyzing and presenting results with AI-based tools.
Course Precondition
Null
Resources
Yılmaz, A. (2024). Yapay Zeka. Kodlab Yayınları.
Notes
Buldaç, M. (2024). DENEYSEL TASARIM SÜRECİNDE YAPAY ZEKÂ ARAÇLARININ KULLANIMI: İÇ MİMARLIK EĞİTİMİNDE BİR DERS MODELİ ÇIKTILARI. Sanat ve Tasarım Dergisi, 14(2), 69-91. Ayaz, O. (2024). Yapay zeka destekli MidJourney görüntü oluşturma modelinin iç mimari tasarım sürecinde değerlendirilmesi üzerine bir bakış (Master's thesis, Mimar Sinan Güzel Sanatlar Üniversitesi, Fen Bilimleri Enstitüsü).
Course Learning Outcomes
Order | Course Learning Outcomes |
---|---|
LO01 | Defines the history of artificial intelligence |
LO02 | Defines types of artificial intelligence |
LO03 | Define data science and prompt engineering and create effective prompts for artificial intelligence models. |
LO04 | Defines the basic principles of artificial intelligence and its application areas in the context of interior architecture/design. |
LO05 | Uses artificial intelligence-supported analysis, planning and decision support tools for interior design. |
LO06 | Uses design and visualization tools supported by artificial intelligence. |
LO07 | Develops design processes practically with the support of artificial intelligence. |
LO08 | Uses visual production and visualization tools effectively in interior design presentations. |
LO09 | Produces creative and sustainable solutions by developing data-driven approaches in design. |
LO10 | Defines the ethical, professional and social impacts of artificial intelligence applications. |
Relation with Program Learning Outcome
Order | Type | Program Learning Outcomes | Level |
---|---|---|---|
PLO01 | Bilgi - Kuramsal, Olgusal | Constantly follows and defines current publications and developments regarding the Interior Architecture profession. | |
PLO02 | Bilgi - Kuramsal, Olgusal | Explains the effects of interior architecture design and applications on universal, social and environmental dimensions. | 4 |
PLO03 | Bilgi - Kuramsal, Olgusal | Distinguishes project and construction site management and practices, environmental and occupational safety issues. | |
PLO04 | Bilgi - Kuramsal, Olgusal | It explains the basic design, history and technical knowledge that can be used in the profession of interior architecture. | |
PLO05 | Bilgi - Kuramsal, Olgusal | Lists the legal consequences of interior architecture applications. | |
PLO06 | Beceriler - Bilişsel, Uygulamalı | Uses visual design elements when preparing reports in the field of Interior Architecture. | 5 |
PLO07 | Beceriler - Bilişsel, Uygulamalı | Evaluates the analyses, findings, results and suggestions of a professional idea or an interior project. | 4 |
PLO08 | Beceriler - Bilişsel, Uygulamalı | Creates/implements contemporary, creative and aesthetic design proposals within realistic physical, social and economic constraints, within the framework of aesthetic values and user needs. | |
PLO09 | Beceriler - Bilişsel, Uygulamalı | It uses modern tools, techniques and technologies regarding design, drawing, software and application in all stages of interior architecture projects from design to implementation. | 5 |
PLO10 | Beceriler - Bilişsel, Uygulamalı | Gains the ability to analyze collected data, synthesize different information and ideas, interpret the results obtained and use them in the interior architecture design process. | 5 |
PLO11 | Beceriler - Bilişsel, Uygulamalı | Gains the ability to be sensitive to the interiors and built environments we live in, and to identify the problems and needs in these spaces with a critical and rational point of view. | |
PLO12 | Beceriler - Bilişsel, Uygulamalı | Within the framework of lifelong learning, they gain the ability to develop themselves in scientific, social, cultural and sports fields. | |
PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Have the ability to work individually and use priority. | 5 |
PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Can follow professional literature and other international developments in interior architecture. | 5 |
PLO15 | Yetkinlikler - Öğrenme Yetkinliği | İç Mimarlık alanının gerektirdiği konularda bilim ve teknolojideki gelişmeleri izleyerek bu gelişmeler doğrultusunda kendisini sürekli yeniler. | 5 |
PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Applies the professional, scientific and ethical responsibility rules concerning the interior architecture profession. | |
PLO17 | Yetkinlikler - Öğrenme Yetkinliği | Uses databases and other information sources effectively in the field of Interior Architecture. | 5 |
PLO18 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | In order to practice the profession of interior architecture, he/she is open to interdisciplinary approaches and makes appropriate use of different disciplines. | 4 |
PLO19 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Have the ability to communicate effectively verbally and in writing in the field of Interior Architecture. | |
PLO20 | Yetkinlikler - Alana Özgü Yetkinlik | Uses theoretical, methodological and applied knowledge in the professional field together to develop interior architectural design suggestions and applications. |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | The history of artificial intelligence. | Research | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
2 | Types of artificial intelligence. | Research | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
3 | Basic principles of artificial intelligence. | Research and Source Reading | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
4 | Data science and prompt creation. | Reading and Resource Reading | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
5 | Interior Architecture and artificial intelligence. | Lecture Notes and Reading Resources | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
6 | Artificial intelligence assisted analysis planning and decision support systems. | Lecture Notes and Reading Resources | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
7 | Artificial intelligence powered web-based tools. | Lecture Notes and Reading Sources | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
8 | Mid-Term Exam | Homework, study, project | Ölçme Yöntemleri: Ödev, Proje / Tasarım |
9 | Artificial intelligence assisted design processes. | Source reading | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
10 | Artificial intelligence assisted design tools 1. | Research, Experience | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
11 | Artificial intelligence assisted design tools 2. | Research, Experience | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
12 | Artificial intelligence-assisted visualization. | Research, Experience | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
13 | Creating an artificial intelligence-supported project 1. | individual work | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
14 | Creating an artificial intelligence-supported project 2. | individual work | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
15 | Creating an AI-supported project 3. | Individual Study | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
16 | Term Exams | Homework/Project Submission Studies | Ölçme Yöntemleri: Ödev, Proje / Tasarım |
17 | Term Exams | Ölçme Yöntemleri: Ödev, Proje / Tasarım |
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 |