Subject Datasheet

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Budapest University of Technology and Economics
Faculty of Transportation Engineering and Vehicle Engineering
1. Subject name Artificial Intelligence vehicles homologation process PhD
2. Subject name in Hungarian Mesterséges Intelligencia alkalmazások homologációs folyamatai és mérései
3. Code BMEKOGGD803 4. Evaluation type exam grade 5. Credits 2
6. Weekly contact hours 2 (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 74
Contact hours 28 Preparation for seminars 14 Homework 5
Reading written materials 5 Midterm preparation 22 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
Opportunities for developing technical intelligence, machine learning and neural networks. Novel challenges and innovative solutions to the homologation process. Self-check process
and the challenges of Automotive AI and the emergence of novel laws. Explore possible solutions to standardize AI vehicle evaluation.
Development of forecasts and forecasts.
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
Self developed materials from the department
Effective date 27 November 2019 This Subject Datasheet is valid for Inactive courses