EXPERIMENTAL ARTIFICIAL INTELLIGENCE APPLICATIONS

SGRA109

Course Code: SGRA109
Semester: -
Theory+Practice: 2 + 2
ECTS: 4

Course Type

Elective Course

Course Level

Bachelor's Degree

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Students will be able to explain the history, evolution, and current applications of artificial intelligence in graphic design.
Students will be able to effectively use AI-based design tools such as Canva, DALL-E, and MidJourney to create original visual content.
Students will be able to analyze and optimize AI-generated designs according to traditional design principles.
Students will be able to evaluate ethical, copyright, and originality issues in AI-assisted design projects.
Students will be able to develop and present a comprehensive design project that integrates AI tools and traditional design techniques.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

Course Description

Course Contents

WEEK	TOPICS
1^st Week	Introduction to AI in Graphic Design & Character Creation
2^nd Week	Researching Historical Characters
3^rd Week	Basics of Character Design
4^th Week	AI Tools for Character Creation
5^th Week	Generating Initial Character Concepts
6^th Week	Refining Character Designs
7^th Week	Storyboarding & Scene Planning
8^th Week	AI-assisted Backgrounds & Scene Elements
9^th Week	Animating Characters
10^th Week	Integrating Character & Scene
11^th Week	Adding Sound and Voice
12^th Week	Editing & Post-production
13^th Week	Final Project Work
14^th Week	Presentation & Critique

Recommended or Required Reading

Character Design for Beginners David Colman Fundamentals of anatomy, expression, and costume design |
Design Basics David A. Lauer & Stephen Pentak Color theory, typography, composition principles |
AI and Creativity: A Timeline Jon McCormack & Oliver Bown (editors) Historical overview of AI in creative fields
The Age of AI YouTube Streaming Platforms Documentary on AI applications
TED Talks on AI in Design Various Speakers Videos on AI and creativity
Online AI Animation Courses Runway ML Academy, Skillshare, LinkedIn Learning Tutorials for AI-assisted animation and storytelling
Free sound libraries FreeSound.org Background music and sound effect
AI Voice Generation Tools Murf.ai, ElevenLabs For narration of short films
Art & Design Communities Behance, ArtStation Visual references and inspiration

Planned Learning Activities and Teaching Methods

Lecture
Uygulama
Project
Presentation

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	40
Total(%)		40
Contribution of In-term Studies to Overall Grade(%)		40
Contribution of Final Examination to Overall Grade(%)		60
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam	1	1	1
Preparation for Quiz
Individual or group work
Preparation for Final exam	14	4	56
Course hours
Preparation for Midterm exam
Laboratory (including preparation)
Final exam	1	1	1
Homework
Presentation (including preperation)	1	3	3
Project	2	30	60
Total Work Load			121
Total Work Load / 30 (h)			4.03
ECTS Credit of the Course			4

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5
K1		X
K2			X
K3	X
K4
K5					X
K6			X		X
K7
K8
K9				X
K10
K11	X
K12
K13
K14
K15
K16
K17	X	X	X	X	X

	LO1	LO2	LO3	LO4	LO5
K1		X
K2			X
K3	X
K4
K5					X
K6			X		X
K7
K8
K9				X
K10
K11	X
K12
K13
K14
K15
K16
K17	X	X	X	X	X

	LO1	LO2	LO3	LO4	LO5
K1		X
K2			X
K3	X
K4
K5					X
K6			X		X
K7
K8
K9				X
K10
K11	X
K12
K13
K14
K15
K16
K17	X	X	X	X	X

	LO1	LO2	LO3	LO4	LO5
K1		X
K2			X
K3	X
K4
K5					X
K6			X		X
K7
K8
K9				X
K10
K11	X
K12
K13
K14
K15
K16
K17	X	X	X	X	X