Information Package / Course Catalogue
Introduction to Artificial Intelligence
Course Code: ELTC184
Course Type: Non Departmental 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

This course aims to teach students the fundamental concepts and historical development of artificial intelligence; introduce the basic approaches of machine learning and deep learning; explain the applications of artificial intelligence in daily life and industry; and raise awareness about generative artificial intelligence, large language models, ethical and legal responsibilities in the use of artificial intelligence, and reliability issues. Furthermore, the course aims to enable students to understand current developments in artificial intelligence and its potential future impact.

Course Content

The concept of artificial intelligence, its historical development and fundamental concepts; ethical and legal responsibilities; basic principles and methods of machine learning and deep learning; applications of artificial intelligence in daily life and industry; generative artificial intelligence and large language models; reliability problems in artificial intelligence systems; opportunities and risks for the future of artificial intelligence, and case studies.

Name of Lecturer(s)
Learning Outcomes
1.To explain the fundamental concepts, historical development, and basic ideas of artificial intelligence.
2.To define machine learning and deep learning approaches at a basic level and explain the relationship between them.
3.To explain the uses of artificial intelligence in daily life and industry with examples.
4.Understanding the fundamental working principles and application areas of generative artificial intelligence and large language models (LLMs).
5.Understanding ethical principles and legal responsibilities in artificial intelligence systems.
6.To understand the reliability, bias, and accuracy problems of artificial intelligence systems at a basic level.
7.To develop a perspective on the future impacts, opportunities, and risks of artificial intelligence.
Recommended or Required Reading
1.Artificial Intelligence Problems - Methods - Algorithms, Seçkin Publishing, ISBN: 9753479859 (Assoc. Prof. Dr. Vasif V. Nabiyev)
2.Deep Learning with Python, Buzdağı Publishing, ISBN: 9786056902420 (François Chollet)
Weekly Detailed Course Contents
Week 1 - Theoretical
The concept of artificial intelligence.
Week 2 - Theoretical
Historical development of artificial intelligence.
Week 3 - Theoretical
Fundamental concepts of artificial intelligence.
Week 4 - Theoretical
Ethical and legal responsibilities in the use of artificial intelligence.
Week 5 - Theoretical
The concept of machine learning.
Week 6 - Theoretical
Machine learning methods. (Quiz)
Week 7 - Theoretical
The concept of deep learning.
Week 8 - Theoretical
Deep learning methods. (Midterm Examination)
Week 9 - Theoretical
Generative artificial intelligence and large language models.
Week 10 - Theoretical
The use of artificial intelligence in daily life.
Week 11 - Theoretical
The use of artificial intelligence in the industrial sector.
Week 12 - Theoretical
The reliability of artificial intelligence. (Assignment)
Week 13 - Theoretical
The future of artificial intelligence: Opportunities and risks.
Week 14 - Theoretical
Overall review and case studies.
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%5
Quiz1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Assignment1415
Quiz1415
Midterm Examination1516
Final Examination1516
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
PÇ-11
PÇ-12
PÇ-13
OÇ-1
3
3
5
OÇ-2
3
3
5
OÇ-3
3
3
5
OÇ-4
3
3
5
OÇ-5
3
3
5
OÇ-6
3
3
5
OÇ-7
3
3
5
Adnan Menderes University - Information Package / Course Catalogue
2026