ARTIFICIAL INTELLIGENCE ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
GEP0616 Traffic and Road Safety Fall 3 0 3 5
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: Tr
Type of course: GE-Elective
Course Level: Bachelor
Mode of Delivery: E-Learning
Course Coordinator : Dr. BURCU ALARSLAN ULUDAŞ
Course Lecturer(s): Instructor RECEP ALİ YÜCE
Course Objectives:

Learning Outputs

The students who have succeeded in this course;

Course Content

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Genel bilgi ve ilgili kaynaklar.
1)
2)
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8) Genel bilgi ve ilgili kaynaklar.
9) Genel bilgi ve ilgili kaynaklar
10) Genel bilgi ve ilgili kaynaklar.
11) Genel bilgi ve ilgili kaynaklar.
12)
13) Genel bilgi ve ilgili kaynaklar.
14)
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16)

Sources

Course Notes:
References: ÖMTC TTI ( Avusturya Yol Güvenliği ) ADAC ( Almanya Yol Güvenliği BMW Rider Academy- Graz Teknik Üniversitesi - MAGNA ( Avusturya Makina- Araç Araştırma ve Geliştirme Kurumu) Googel -Waymo Sürücüsüz araçlar.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance % 0
Laboratory % 0
Application % 0
Field Work 0 % 0
Special Course Internship (Work Placement) 0 % 0
Quizzes 11 % 40
Homework Assignments 0 % 0
Presentation % 0
Project 0 % 0
Seminar 0 % 0
Midterms % 0
Preliminary Jury 0 % 0
Final 1 % 60
Paper Submission 0 % 0
Jury 0 % 0
Bütünleme % 0
Total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 10 4 40
Presentations / Seminar 0 0 0
Project 0 0 0
Homework Assignments 0 0 0
Quizzes 11 4 44
Preliminary Jury 0 0 0
Midterms 0 0 0
Paper Submission 0 0 0
Jury 0 0 0
Final 1 2 2
Total Workload 128

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Have sufficient background in mathematics, science and artificial intelligence engineering.
2) Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions.
3) Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose.
4) Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction.
5) Select and use modern techniques and tools necessary for engineering applications.
6) Design and conduct experiments, collect data, and analyse and interpret results.
7) Work effectively both as an individual and as a multi-disciplinary team member.
8) Access information via conducting literature research, using databases and other resources
9) Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning.
10) Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field.
11) Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level.
12) Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age.
13) Have a sense of professional and ethical responsibility.
14) Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices.