Published standards define the competency frameworks, evaluation criteria, and assessment methodologies for each certification domain. All standards are versioned, publicly reviewable, and updated on an annual cycle.
Defines the competency framework, evaluation criteria, and assessment methodology for AI evaluation professionals. Covers benchmark design, model assessment, adversarial testing, and performance measurement across six core domains.
Establishes requirements for AI safety engineering competence, including risk assessment, safety protocol design, containment strategies, monitoring systems, and incident response planning.
Defines competency requirements for AI governance professionals, covering governance framework design, alignment assessment methodology, policy development, and regulatory compliance.
Establishes the framework for certifying calibrated human judgment, cognitive assessment, and decision quality in AI-augmented contexts. Backed by the Human Assessment of Performance and Intelligence (HAPI) framework.
The overarching evaluation framework governing all Certificate.School certifications. Defines the multi-layer evaluation pipeline, quality assurance processes, oversight model, and governance requirements.
Technical specification for enterprise-grade credential validation, including API endpoints, verification workflows, and integration requirements for organizational adoption.