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DTSTART:20251026T030000
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UID:2549111a-7ac8-4a37-b111-976cc1c68afb
DTSTAMP:20260410T204054Z
CATEGORIES:Verification\, Analyses and Testing
CLASS:PUBLIC
DESCRIPTION;ALTREP="CID:<FFFF__=0ABBE548DFE235B58f9e8a93d@coffeebean.com>":
 \n\n\n\n\n\nSimulate your System with Bayesian Networks\nISO 21448 - Safet
 y of the Intended Functionality (SOTIF) requires measurable acceptance cri
 teria but does not tell us how to validate those.\nThis training is fully 
 focused on practical answers how to …\n\nquantify performance limitations 
 and risks\nidentify hidden performance insufficiencies\nminimize uncertain
 ty\nfind unknown scenarios &amp\; rare hazardous events\ndetermine probabi
 lities &amp\; occurrence rates of hazardous events\nmodel complex\, multi-
 dimensional dependencies &amp\; conditional probabilities\n\nEven brute-fo
 rce simulation similar to computer games is not a solution\, as it does no
 t quantify uncertainties and statistical dependencies based on a solid mat
 hematical foundation.\nWe provide you with a modern computer-based validat
 ion method of SOTIF acceptance criteria which scales to today´s real autom
 otive systems and allows to simulate the complete system with parameters r
 eflecting real-world scenarios.\nWhy Attend?\n\nLearn how to model uncerta
 inty\nOvercome the limits to traditional risk assessment approaches\nUse n
 ew technology like Bayesian Networks for highly complex systems in real-wo
 rld scenarios\nquantify performance limitations and risks\n\n\n\n\n\n\n\n
 \nWho should attend?\n\n\n\nProduct Owners\, Function Owners\, Domain Expe
 rts for AD Systems\nSystem &amp\; SW Engineers\nExperts for Functional Saf
 ety and SOTIF\n\nApplicable for Autonomous Driving as well as for other ar
 eas that require quantitative risk analysis.\nAgenda and Content\n\nMotiva
 tion\n\nMillions of km for Driving-Tests?\nLimits of classic risk analysis
  &amp\; common cause\n\n\nModern Methods – Basics &amp\; Theory\n\nEssenti
 al Statistical Concepts – Quick Refresher\nModel Statistical System Depend
 encies\nBayesian Networks\n\n\nPractical Application\n\nModeling a real SO
 TIF application\nSimulation\, System Optimization and Tuning\n\n\n\nAccomp
 anied by a practical example and hands-on exercises with Python &amp\; Jup
 yter\nPrerequisites: \n\nTechnical Background (Bachelor/Master level)\nBas
 ic Programming Experience (Python or similar)\n\nRecommended: Exercises ca
 n be performed on your own laptop (quick setup guidelines for Python are p
 rovided)\nTakeaway:\nAfter this training\, you´ll be able to model and sim
 ulate SOTIF systems in real-world scenarios\, to optimize and validate you
 r system based on proven mathematical methods.\n \nDuration: 2 days\n\n\n
 \nSchedule: 1st day between 10:00 and 18:00\; 2nd day between 9:00 and 17:
 00\; \n                 Time zone:Europe/Berlin\,Display:(UTC+02:00)\n \nP
 rice: 1890\,00€\nLanguage: Depending on the participants the training will
  be given in German or English. The training material will be in English\n
 Location: ONLINE or exida.com GmbH office\, Prof.-Messerschmitt-Str. 1\, 8
 5579 Neubiberg / Germany \nCertificate: each participant gets a letter of 
 attendance.\n\n
DTSTART:20260624T080000Z
DTEND:20260625T150000Z
GEO:+48.0755;+11.656484
LOCATION:Prof.-Messerschmitt-Straße 1 - 85579 Neubiberg / Germany
ORGANIZER;CN=:kerstin.tietel@exida.com
SEQUENCE:1
SUMMARY:Modern Computer-Based Validation of SOTIF Acceptance Criteria (ISO 
 21448) (DE0291)
TRANSP:OPAQUE
URL:https://www.exida-eu.com/all-trainings/385-modern-computer-based-iso-21
 448-de0291
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