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AI Security Fundamentals: Risks, Frameworks & Tools

Master AI threat modeling, SDLC integration, and compliance for enterprise systems with Andrii Piatakha on Udemy.

🎯 Lo que aprenderás y dominarás

AI threat modeling methodologies
Integrating security into ML pipelines
Defending against common AI attack vectors
Compliance mapping for enterprise AI systems
Risk assessment and mitigation strategies
Monitoring and governance practices

📖 Descripción del curso y temario

This course delivers practical grounding in AI security without hand-waving. Piatakha walks through threat modeling concrete examples, showing how to map risks to the software development lifecycle. The framework sections are grounded and actionable, covering data poisoning, adversarial attacks, and model monitoring. It is particularly strong on mapping security controls to compliance requirements, making it valuable for teams building production AI systems. The balance of theory and hands-on exercises ensures you can immediately apply the concepts to real-world projects.

📚 Estructura del plan de estudios

5 módulos principales

📋 Requisitos y conocimientos previos

  • Basic understanding of machine learning concepts
  • Familiarity with software development processes

💼 Salidas laborales y puestos objetivo

AI Security Engineer Machine Learning Operations Specialist Compliance Analyst

Preguntas frecuentes (FAQ)

AI Security Fundamentals: Risks, Frameworks & Tools
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Duración: 8 total hours
Credencial: Completion certificate
Idioma: English
Instructor: Andrii Piatakha

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