| Course Type | Elective Course |
|---|
| Course Level | Bachelor's Degree |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 4 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Understand the fundamental concepts and principles of artificial intelligence.
- Recognize the various applications of artificial intelligence in design.
- Utilize AI-based design tools and methods.
- Evaluate the ethical and social implications of artificial intelligence.
- Generate creative and innovative solutions by using AI in their own design projects.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
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| Recommended Optional Programme Components | |
|---|
| Course Description | The objective of this course is to introduce students to the potential and applications of artificial intelligence in design, to enable them to explore AI-based design tools and methods, and to encourage them to develop their own design projects using these tools. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Introductory session: Course syllabus review and introductions. |
|
2nd Week |
What is artificial intelligence? A historical overview of artificial intelligence, and its influence on the field of design. |
|
3rd Week |
A Taxonomy of Artificial Intelligence Algorithms: Machine learning, Deep learning, Artificial neural networks, Natural language processing, and Computer vision. |
|
4th Week |
The Intersection of Artificial Intelligence and Design: AI integration in design, ideation and concept generation, prototyping, user testing, UX design, manufacturing, and deployment. |
|
5th Week |
AI-Powered Design Tools: Generative design tools, Automated layout and optimization tools, Personalization and adaptation tools, Data-driven design tools |
|
6th Week |
Case Studies: Examples of AI applications in various design fields. Product design, Visual communication design, Architectural design, Fashion design |
|
7th Week |
Ethics of AI in Design: Ethical use of AI, Bias and discrimination risks, Transparency and accountability, Human-machine collaboration. |
|
8th Week |
Midterm exam |
|
9th Week |
Ethical and Social Implications of AI in Design: Bias and discrimination, Transparency and accountability, Privacy and data security, Impacts on the workforce. |
|
10th Week |
The Future of AI in Design: AI's future in design, New opportunities and challenges for designers. |
|
11th Week |
Guest speaker |
|
12th Week |
Group Project - AI-Based Design Application: Students will work in small groups to develop a solution to a design problem using artificial intelligence. |
|
13th Week |
Group Project - AI-Based Design Application: Students will work in small groups to develop a solution to a design problem using artificial intelligence. |
|
14th Week |
Final Exam |
|
| Recommended or Required Reading | Yapay Zeka İle Gelişen Tasarım: Grafik ve Oyun Tasarımı, Otonom Sanat, Metaverse ve NFT Olasılıklarını Keşfetmek, Dr. Öğretim Üyesi İsmail Ergen EFE AKADEMİ YAYINLARI |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Discussion
- Practice
- Presentation
- Report Preparation
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
25 |
| Project |
1 |
20 |
| Total(%) |
|
45 |
| Contribution of In-term Studies to Overall Grade(%) |
|
45 |
| Contribution of Final Examination to Overall Grade(%) |
|
55 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
3 |
3 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
3 |
42 |
| Preparation for Final exam |
1 |
4 |
4 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
6 |
6 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
3 |
3 |
| Homework |
|
|
|
| Project |
2 |
10 |
20 |
| Total Work Load | 120 |
| Total Work Load / 30 (h) | 4 |
| ECTS Credit of the Course | 4 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
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