Information Package / Course Catalogue
Artificial Intelligence Applications in the Automotive Industry
Course Code: OTT113
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 1
Prt.: 1
Credit: 2
Lab: 0
ECTS: 2
Objectives of the Course

This course is designed to teach students the fundamental concepts of artificial intelligence technologies and explain how these technologies can be used in the automotive industry. It also aims to help them understand the ethical, social, and economic dimensions of artificial intelligence.

Course Content

This course covers the fundamentals of artificial intelligence and its application in automotive technology, how the processes that make up automotive systems can be managed with AI applications, its use in design processes, shaping user experiences with AI applications, AI ethics and safety issues, and future AI trends and design directions.

Name of Lecturer(s)
Learning Outcomes
1.Ability to effectively apply machine learning and deep learning technologies.
2.Ability to present industry-related designs using technological devices.
3.Developing artificial intelligence applications in automotive technology.
4.The ability to interpret the performance process in internal combustion engines through artificial intelligence applications.
5.Ability to interpret the effects of artificial intelligence applications in motor vehicles on autonomous driving.
Recommended or Required Reading
1.RUSSEL, S., & NORVING, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
2.TOSUN, B. (2021). Digital Transformation and Design. Beta Publications.
Weekly Detailed Course Contents
Week 1 - Preparation Work
Introduction and Basic Concepts
Week 2 - Theoretical
Types of Artificial Intelligence
Week 3 - Theoretical & Practice
Machine Learning and Deep Learning
Week 4 - Theoretical & Practice
Data and Data Analytics
Week 5 - Theoretical & Practice
Design Process and Artificial Intelligence
Week 6 - Theoretical & Practice
User Experience and Artificial Intelligence
Week 7 - Theoretical & Practice
Interaction of artificial intelligence in automotive fuel system technology.
Week 8 - Intermediate Exam
Midterm Exam (Visa)
Week 9 - Theoretical & Practice
Performance interaction of artificial intelligence applications in internal combustion engines.
Week 10 - Theoretical & Practice
The effects of artificial intelligence applications in motor vehicles on autonomous driving performance.
Week 11 - Theoretical & Practice
The effects of artificial intelligence applications in automotive technology on fuel consumption.
Week 12 - Theoretical & Practice
The impact of artificial intelligence applications in automotive technology on safety systems.
Week 13 - Theoretical & Practice
The impact of artificial intelligence applications in electric and hybrid vehicle technologies.
Week 14 - Final Exam
End-of-Term Exam (Final)
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%5
Quiz1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140342
Assignment1011
Quiz1011
Midterm Examination1213
Final Examination1213
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
OÇ-1
4
2
5
5
5
4
4
2
4
4
4
OÇ-2
3
5
3
4
4
5
3
3
5
5
4
OÇ-3
4
4
2
3
4
5
5
3
3
5
4
OÇ-4
3
3
3
5
5
4
2
4
5
5
5
OÇ-5
4
2
4
3
5
2
4
3
4
5
3
Adnan Menderes University - Information Package / Course Catalogue
2026