Subject Datasheet

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Budapest University of Technology and Economics
Faculty of Transportation Engineering and Vehicle Engineering
1. Subject name Application of AI in vehicle industry PhD
2. Subject name in Hungarian Neurális hálók járműipari alkalmazása
3. Code BMEKOGGD805 4. Evaluation type exam grade 5. Credits 3
6. Weekly contact hours 3 (0) Lecture 0 (0) Practice 0 (0) Lab
7. Curriculum
PhD Programme
8. Role
Specific course
9. Working hours for fulfilling the requirements of the subject 90
Contact hours 14 Preparation for seminars 14 Homework 12
Reading written materials 20 Midterm preparation 30 Exam preparation 0
10. Department Department of Automotive Technologies
11. Responsible lecturer Dr. Zöldy Máté
12. Lecturers Dr. Zöldy Máté
13. Prerequisites  
14. Description of lectures
Artificial Intelligence is based on applications in the automotive industry. Machine Learning and Neural Networks for Homologization. Automotive AI Use Cases. Market barriers and challenges a
AI forecasts for automotive applications in neural networks.
15. Description of practices
16. Description of labortory practices
17. Learning outcomes
A. Knowledge
  • Is familiar with the images presented in the subject and the individual procedures of the internal relationships.
B. Skills
  • Capable of all procedures and research.
C. Attitudes
  • Openness to new opportunities in the field.
D. Autonomy and Responsibility
  • Autonomy and responsibility: a vehicle for solving research task.
18. Requirements, way to determine a grade (obtain a signature)
Knowing the curriculum and application of it. The exam is oral.
19. Opportunity for repeat/retake and delayed completion
There is one occasion to retake the exam.
20. Learning materials
Autonomous Vehicle Driverless Self-Driving Cars and Artificial Intelligence: Practical Advances in AI and Machine Learning
Effective date 27 November 2019 This Subject Datasheet is valid for Inactive courses