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πΆ Intermediate
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4.4 (33 reviews)
AI Security Fundamentals: Risks, Frameworks & Tools
Master AI threat modeling, SDLC integration, and compliance for enterprise systems with Andrii Piatakha on Udemy.
π― What You Will Learn & Master
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AI threat modeling methodologies
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Integrating security into ML pipelines
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Defending against common AI attack vectors
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Compliance mapping for enterprise AI systems
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Risk assessment and mitigation strategies
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Monitoring and governance practices
π Course Overview & Syllabus Review
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.
π Structured Curriculum Breakdown
5 Core Modulesπ Prerequisites & Requirements
- Basic understanding of machine learning concepts
- Familiarity with software development processes
πΌ Target Career & Job Roles
AI Security Engineer
Machine Learning Operations Specialist
Compliance Analyst
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Duration:
8 total hours
Credential:
Completion certificate
Language:
English
Instructor:
Andrii Piatakha