Information Package / Course Catalogue
Artificial Intelligence and Business Applications
Course Code: ISL446
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

The aim of this course is to raise awareness among students about the concept of artificial intelligence, its processes and applications in businesses, and to provide them with basic skills in artificial intelligence.

Course Content

Explaining artificial intelligence, explaining its basic logic and historical development, conveying the usage areas of artificial intelligence in different disciplines, explaining the logic of artificial intelligence analysis, explaining the purposes of artificial intelligence and the methodologies used to achieve these purposes, explaining the effects of artificial intelligence on social, technological and economic change, artificial intelligence. The aim is to convey the relationship between intelligence and ethics and to provide information about the development process of artificial intelligence in the future.

Name of Lecturer(s)
Lec. Esin SAYIN
Learning Outcomes
1.Interprets the process of establishing corporate quality culture.
2.Defines areas of AI application in business.
3.Describes the relationship between data analytics and machine learning.
4.Analyzes AI-supported decision systems.
5.Evaluates ethical and privacy issues.
6.Examines AI applications in business through case studies.
Recommended or Required Reading
1.Ali Şir Atilla, Artificial Intelligence Technology and Applications, Dikeyeksen PUBLISHING, İSTANBUL, 2022.
2.Çetin Elmas, artificial intelligence applications, Seçkin Publishing, İSTANBUL, 2021.
Weekly Detailed Course Contents
Week 1 - Theoretical
What is Artificial Intelligence? Historical Development and Philosophy
Week 2 - Theoretical
Change Process with Artificial Intelligence (Professional change, social changes)
Week 3 - Theoretical
Artificial Intelligence Application Areas (Natural Language processing, computer vision, decision making, problem solving, voice recognition…)
Week 4 - Theoretical
How Does Artificial Intelligence Learn?
Week 5 - Theoretical
Big Data (Data Mining, Text Mining, Learning Analytics…)
Week 6 - Theoretical
Programs and Applications Used in Artificial Intelligence Applications
Week 7 - Theoretical
Expert Systems
Week 8 - Theoretical
Areas of Use and Examples of Artificial Intelligence I (Manufacturing Enterprises)
Week 9 - Theoretical
Areas of Use and Examples of Artificial Intelligence II (Service Enterprises)
Week 10 - Theoretical
Areas of Use and Examples of Artificial Intelligence III (Education & Schools)
Week 11 - Theoretical
Artificial Neural Networks and Heuristic Techniques
Week 12 - Theoretical
Artificial Intelligence and Ethics
Week 13 - Theoretical
Future Predictions in Artificial Intelligence
Week 14 - Theoretical
Future Predictions in Artificial Intelligence
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142370
Midterm Examination125126
Final Examination130131
TOTAL WORKLOAD (hours)127
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
2
2
2
4
2
2
2
2
3
1
OÇ-2
2
2
3
4
3
2
2
2
2
1
OÇ-3
2
3
2
3
3
2
2
3
4
1
OÇ-4
2
2
2
3
3
2
2
3
3
1
OÇ-5
1
1
4
2
1
1
2
2
1
1
OÇ-6
2
2
2
4
3
2
2
3
3
1
Adnan Menderes University - Information Package / Course Catalogue
2026