Prerequisites
- UL Certified Artificial Intelligence Professional.
- Foundations training for practical experience in the development of ML-models.
- Prior knowledge of SOTIF (ISO 21448) and functional safety (ISO 26262).
Autonomy Safety
UL Certified Autonomy Safety Professional Training in Machine Learning
This two-day training is focused on machine learning for automotive safety, and the state-of-the-art safety frameworks used for automotive.
This two-day training course is dedicated to machine learning (ML) for automotive safety. It provides guidance for the development of ML components into the safety frameworks used for automotive, including functional safety (FuSa) and safety of the intended functionality (SOTIF).
This training also includes the reference information of novel autonomy safety standards, including:
- UL 4600, the Standard for Evaluation of Autonomous Products.
- ISO/TR 4804:2020, Road Vehicles - Safety and Cybersecurity for Automated Driving Systems - Design, Verification and Validation.
- ISO/IEC DTR 5469, Artificial intelligence - Functional safety and AI systems.
- ISO/AWI PAS 8800, Road Vehicles - Safety and Artificial Intelligence.
- ISO/IEC TR 24029-1:2021, Artificial Intelligence (AI) - Assessment of the Robustness of Neural Networks - Part 1: Overview.
- ISO/IEC DIS 24029-2, Artificial intelligence (AI) - Assessment of the Robustness of Neural Networks - Part 2: Methodology for the Use of Formal Methods.
Key Takeaways
Day 1
- Introduction.
- Automotive safety and AI standards.
- Deployment of AI into systems.
- Factors to consider for AI safety.
- Running example.
- Specification and design (SOTIF-specific).
- AI safety culture.
- Concept phase.
- System development phase
Day 2
- Hardware development phase.
- Software development phase.
- Verification and validation (V&V) strategy.
- Software verification phase.
- Hardware verification phase.
- System verification phase.
- Vehicle verification and validation phase.
- Assessment.
- Operations, decommissioning, service and maintenance.
Target Audience
Engineers working with advanced driver assistance systems (ADAS) and autonomous vehicles (AV), including:
- Automotive engineers.
- Safety engineers.
- Data scientists.
- Project leaders.
- Testing personnel.
Examination
Participants who complete training can take a two-hour certification exam on the morning of the third day. Those who pass the exam are individually certified as a UL Certified Autonomy Safety Professional – Machine Learning or UL-CASP. Upon successful completion of the UL-CASP exam, participants receive a certificate and badge they can use to demonstrate their competence in Machine Learning. The certification is good for three years, after which individuals may recertify.
Further Information
For online trainings, all materials are offered digitally. For in-person trainings, all materials are offered digitally and may be supplemented with hard copies. Copies of any relevant standards must be provided by the learner.
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