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Certified AI Reliability & Safety Engineer (CAIRSE)
The "Certified AI Reliability & Safety Engineer (CAIRSE)" program equips engineers to ensure AI systems are reliable and safe under all operating conditions. Participants learn to integrate fail-safes and robust security mechanisms. The course emphasizes cybersecurity practices that protect AI systems against malicious interference, enhancing operational integrity and user trust.
Provider Information
Tonex, Inc.
6275 W. Plano Parkway, Suite 500
Plano, TX 75093
Course Overview
None
Learning Objectives
- Understand the principles of AI reliability, safety, and robustness.
- Design and implement testing methodologies for AI safety and resilience.
- Identify and mitigate potential failure modes and risks in AI systems.
- This course directly impacts cybersecurity by enabling the development of AI systems that are resilient to failures and adversarial inputs, making them inherently more secure against manipulation and attacks.
- Develop strategies for continuous monitoring and improvement of AI safety performance.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.