Akademik Dersler - Tanıtım

Course Introduction Information


Code - Course Title	ENT3518 - Artificial Intelligence in Design Process
Course Type	Area Elective Courses
Language of Instruction	Türkçe
Laboratory + Practice	2+1
ECTS	4.0
Course Instructor(s)	DOÇENT DOKTOR ENGİN KAPKIN
Mode of Delivery	This course is offered in face-to-face mode only. Unless otherwise stated, classes will be conducted as follows:1- Students are expected to come prepared by completing the provided readings, videos, or homework assignments that serve as preparation for class.2- The course begins with a summary of the previous week.3- Students share all their ideas and questions (good and bad) with their peers in the classroom. These ideas and evaluations are then analyzed and critiqued as a class.4- The course topic is explained and demonstrated to the students, and then comments and questions are received.5- The weekly homework assignment is announced.6- The course concludes with the announcement of the next week's topic.Questions and problems are discussed continuously during class.
Prerequisites	There is no prerequisite or co-requisite for this course.
Courses Recomended	It is recommended that this course be taken after the second year. Successful completion of the "Computer Aided Design" courses is essential before taking this course.
Required or Recommended Resources
Recommended Reading List	The course reading list, worksheets and materials will be announced to students weekly.
Assessment methods and criteria	Class attendance is mandatory. Attendance will be assessed at the beginning of each class. Class attendance and engagement grades are assessed for arriving at class on time, bringing the necessary materials, and being active during class. Responsibility grades are assessed for completing and submitting assignments and practical exercises on time, and for communicating any special circumstances with the instructor on time or in advance. All assignments are due within one week of their assignment date, unless otherwise specified in the course schedule or by the instructor. Late work will not be accepted unless agreed upon with the instructor in advance, and a grade of "Zero (0)" will be assigned.The course is a hands-on course. Students will be assessed based on the drawings and projects they prepare during class. All reports, drawings, models, and presentations created during the design process will be included in the assessment. Grading percentages may vary by semester.Attendance, engagement, and engagement grades: 5%Average of quizzes and assignments: 15%1st Midterm Exam: 30%Final Exam: 50%
Work Placement	A project will be developed within the scope of the course.
Sustainability Development Goals

Content

Weeks	Topics
Week - 1	Introduction and Course Introduction: Course scope, expectations, evaluation criteria, and the role of artificial intelligence in design
Week - 2	Introduction to Design Thinking: Stages of design thinking: discovery, definition, ideation, prototyping, testing
Week - 3	Fundamentals of Artificial Intelligence: Definition, history, types of artificial intelligence, and its general potential in the context of industrial design
Week - 4	Discovery Phase: AI-powered user research, analytics tools, data collection tools
Week - 5	Defining the Problem: Delimiting the problem area, synthesis with text-based AI, creating a problem framework and project statement
Week - 6	Idea Development Stage: Creative thinking techniques and idea generation processes with artificial intelligence
Week - 7	Developing Ideas with Visual Production Tools I: Using visual AI tools like Midjourney, DALL·E, Firefly – hands-on workshop
Week - 8	Developing Ideas with Visual Production Tools II: Generating variations with AI tools, style experiments, conceptual design alternatives
Week - 9	Prototyping Phase: Rapid modeling tools, 3D production scenarios, form creation with artificial intelligence
Week - 10	Testing Phase: Testing process with creating user scenarios, data analysis and prediction models
Week - 11	Process Documentation and Reporting: Preparing AI-supported presentation materials, process documentation, automatic content generation
Week - 12	Project Development: Each student or group develops an AI-powered design project – Phase 1: research & problem definition
Week - 13	Project Development: Phase 2: ideation, prototyping and testing
Week - 14	Project Development: Stage 3: Presentation of project outcomes, evaluator and peer feedback, overall evaluation

Learning Activities and Teaching Methods

Teaching Methods
Lecture
Question & Answer
Demonstration
Experiment
Drill - Practise
Problem Solving
Brain Storming
Proje Design/Management
Competences
Productive
True to core values
Rational
Creative
Follow ethical and moral rules
Effective use of a foreign language
Work in teams
Use time effectively
Eleştirel düşünebilme
Abstract analysis and synthesis
Problem solving
Information Management
Decision making
Project Design and Management

Assessment Methods

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
Toplam (%)		0