Algorithm Auditing & Assurance
This course teaches how to apply proven regulatory audit and assurance standards to the rapidly evolving field of AI and algorithmic systems. Learn how to navigate the complexity of AI-driven decision-making systems by understanding audit planning, risk assessment, evidence gathering, and reporting in the context of algorithm assurance.
Les objectifs
Le public ciblé
This course is ideal for:
- AI auditors and compliance professionals
- Risk analysts and AI assurance experts
- Policy and legal professionals in AI governance
- Data protection officers (DPOs) and ethics officers
- Technology consultants and business leaders responsible for AI governance
Les prérequis
- No coding experience required (familiarity with Python is helpful)
- Basic knowledge of AI concepts and data processing beneficial
- English proficiency required
- Strong critical thinking and analytical skills recommended
This course is designed to be accessible to professionals from non-technical backgrounds.
Le contenu de la formation
Informations importantes
This course is part of BABL AI’s AI & Algorithm Auditor Certification Program, which offers a comprehensive foundation in AI auditing, risk management, and regulatory compliance.
Price: $599 one time purchase. Special price for TÜV Rheinland with a 30% discount: $419,3.
FAQ Suggestions
1. Do I need programming skills to take this course?
No. The course is designed for non-technical professionals, though familiarity with programming or Python may be helpful.
2. How is this course different from general AI auditing courses?
This course focuses specifically on applying traditional audit and assurance practices to modern AI and algorithmic systems.
3. What practical skills will I gain?
You will learn how to conduct structured audits, assess risk, collect evidence, and issue assurance opinions for AI systems.
Choix de la session
Algorithm Auditing & Assurance
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>1 000 sessionsDifférents formats selon vos besoins : inter/intra-entreprise, e-learning, des formations sur mesure s'appuyant sur des études de cas pratiques, ...
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