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Udemy
πΆ Intermediate
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4.9 (13 reviews)
Securing AI Applications: From Threats to Controls
Defend generative AI systems with firewalls, SPM, and data governance controls
π― What You Will Learn & Master
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Identify common threat vectors targeting generative AI systems
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Configure AI firewalls and security posture management tools
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Implement data governance frameworks for model training
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Mitigate prompt injection and adversarial attacks
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Secure model deployment pipelines and runtime environments
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Evaluate and improve overall AI security posture
π Course Overview & Syllabus Review
This course provides a practical deep-dive into protecting generative AI systems from emerging threats. Andrii Piatakha explains how to deploy AI firewalls and implement Security Posture Management to monitor model behavior. The modules on data governance walk through concrete strategies for securing training pipelines and preventing prompt injection attacks. While the content is technically dense, the instructor breaks down complex concepts like model hallucination mitigation into actionable steps. Ideal for developers and security engineers who need to move beyond basic awareness and build actual defenses for their AI applications.
π Structured Curriculum Breakdown
6 Core Modulesπ Prerequisites & Requirements
- None
πΌ Target Career & Job Roles
AI Security Engineer
Machine Learning Operations Specialist
Cybersecurity Analyst
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Duration:
8 total hours
Credential:
Completion certificate
Language:
English
Instructor:
Andrii Piatakha