COURSE UNIT TITLE

: DIGITAL ART AND PHOTOGRAPHY PRACTICE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
FTZ 3044 DIGITAL ART AND PHOTOGRAPHY PRACTICE COMPULSORY 2 2 0 6

Offered By

Photography

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

MURAT KOCAKAPLAN

Offered to

Photography

Course Objective

The aim is to teach visual production in the field of digital art using photography applications and artificial intelligence technologies. It is to enable students to understand contemporary techniques and methods in digital art and effectively utilize these techniques in the art of photography.

Learning Outcomes of the Course Unit

1   To be familiar with the basic concepts of artificial intelligence and understand AI applications used in photography.
2   To apply artificial intelligence algorithms such as Midjourney and Stable Diffusion in the context of photo realism.
3   To access databases and query and analyze images using artificial intelligence algorithms.
4   To understand prompt writing techniques and effectively utilize them in visual production.
5   To be able to generate visuals using algorithms for text-to-image and image-to-image transformations.
6   To enhance the ability to apply what has been learned through individual or collaborative projects.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Digital art and photography
2 Prompt writing techniques
3 Prompt creation strategies and generating visuals from text
4 Midjourney applications and their use in photo realism
5 Midjourney applications and their use in photo realism
6 Data preparation for Stable Diffusion applications
7 Stable Diffusion algorithm and its use in photo realism
8 Accessing and utilizing databases
9 Image generation techniques from visual to visual (image-to-image)
10 Midterm exam (Application)
11 Determining project topics
12 Project development
13 Project development
14 Project development/Presentations

Recomended or Required Reading

Lecture notes and presentations
Online resources and articles
Books and other printed materials
Libraries and information centers
Museums and art galleries
Online courses and tutorials
Communication with artists and researchers

Planned Learning Activities and Teaching Methods

Theoretical Lessons (2 Hours):

Exposition: Basic concepts, techniques, and methods will be explained through presentations, videos, and examples.
Discussion: Current developments, ethical and aesthetic issues will be addressed through class discussions.
Guest Speakers: Experts in the field such as artists and researchers will be invited to give lectures.
Practical Lessons (2 Hours):

Workshop Activities: Students will practice using AI tools through hands-on exercises.
Project Development: Individual or group projects will be conducted to reinforce learning.
Exhibitions and Presentations: Student projects will be shared through exhibitions and presentations.
Learning and Teaching Methods:

Active Learning: Students' active participation and experiential learning will be encouraged.
Inquiry-Based Learning: Curiosity and research will be encouraged.
Feedback: Continuous and constructive feedback will be provided.
Use of Technology: Various digital tools and platforms will be used.
Assessment:

Participation and Activity: Class participation, assignments, and projects will be evaluated.
Midterm Exam/Practical: A midterm exam/practical will be conducted to assess theoretical knowledge.
Final Project: Individual or group projects will provide a comprehensive assessment of learning.
Additional Resources:

Lecture notes and presentations will be shared on an online platform.
Students will be recommended online resources and articles related to digital art and photography.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 PRC PRACTICE
2 ASG ASSIGNMENT
3 FCG FINAL COURSE GRADE PRC * 0.50 + ASG * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Theoretical Knowledge: Theoretical knowledge demonstrated in the midterm exam and project presentation.
Technical Skills: Proficiency in using AI tools and techniques.
Creativity and Originality: Creativity and originality in visual productions.
Concept and Content: Conceptual and contentual depth of visual productions.
Research and Experimentation: Ability to research different AI artists and their work and to experiment.
Presentation: Clarity, impact, and originality of visual and written presentations.

Language of Instruction

Turkish

Course Policies and Rules

Class attendance and completion of in-class applications are mandatory.

Contact Details for the Lecturer(s)

murat.kocakaplan@deu.edu.tr
05418930706

Office Hours

Thursday 15:00-16:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 2 24
Tutorials 12 2 24
Preparations before/after weekly lectures 12 6 72
Preparation for quiz etc. 2 8 16
Project Assignment 1 4 4
Practical exam 1 4 4
TOTAL WORKLOAD (hours) 144

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15PO.16PO.17PO.18PO.19PO.20
LO.15543
LO.2
LO.355
LO.4543
LO.555
LO.6555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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