Information Package / Course Catalogue
Artificial Intelligence Knowledge
Course Code: MUH008
Course Type: Area Elective
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 2
Objectives of the Course

The aim of this course is to enable students to learn the fundamental concepts of artificial intelligence and to consciously use AI tools in professional processes within the industry.

Course Content

Analyzing how today's technology works. Correctly interpreting newly developed technologies. Using technological devices in the most efficient and comprehensive way. Knowing the working principles of a technological device and making the right additions.

Name of Lecturer(s)
Learning Outcomes
1.Ability to analyze developing technology
2.Ability to contribute to new product development.
3.Ability to model in the field.
4.Ability to manage projects
5.Developing projects with the right moves
Recommended or Required Reading
1.Instructor's Lecture Notes
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to artificial intelligence
Week 2 - Theoretical
Artificial intelligence from yesterday to today.
Week 3 - Theoretical
Chat GPT Application
Week 4 - Theoretical
Chat GPT Application
Week 5 - Theoretical
Gemini App
Week 6 - Theoretical
Gemini App
Week 7 - Theoretical
Dall.E Application
Week 8 - Theoretical
Dall.E Application
Week 9 - Theoretical
Scholar GPT Application
Week 10 - Theoretical
Scholar GPT Application
Week 11 - Theoretical
Microsoft Copilot Application
Week 12 - Theoretical
Microsoft Copilot Application
Week 13 - Theoretical
ImageBind Application
Week 14 - Theoretical
ImageBind Application
Assessment Methods and Criteria
Type of AssessmentCountPercent
Presentation1%5
Term Assignment1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory141128
Lecture - Practice140114
Midterm Examination1314
Final Examination1314
TOTAL WORKLOAD (hours)50
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
5
4
OÇ-2
3
OÇ-3
3
2
OÇ-4
OÇ-5
Adnan Menderes University - Information Package / Course Catalogue
2026