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Secure AI Interpret and Protect Models · LearnSpace
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courseraПрограммирование

Secure AI Interpret and Protect Models

Курс от Coursera
Средний≈ 5.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Ever wonder if your smart AI is actually secure? In this course, we'll ditch the dry theory to show you how to build genuinely resilient AI systems from the ground up, making security a core part of your design, not just an afterthought. You'll begin by stepping into the role of an AI Security Architect, running a “pre-mortem” to think like an attacker and neutralize threats before they even happen. Through focused videos and exercises, you’ll master essential defenses like blocking bad data with input sanitization, ‘vaccinating’ your model against attacks with adversarial training, and protecting user data with differential privacy. This all culminates in a hands-on lab where you'll personally fix a vulnerable model and prove its new resilience. The main goal is to shift your mindset from reactive patching to proactive design, so you’ll walk away with the real-world skills to analyze defense strategies, successfully harden a model in a lab, and design a comprehensive security plan for any new AI project. This course is for AI developers, security engineers, MLOps specialists, and data scientists aiming to master securing AI models against adversarial threats. Proficiency in Python and a machine learning framework (e.g., TensorFlow, PyTorch). Foundational knowledge of building and training AI models. By the end of this course, you’ll have gained the skills to thoroughly analyze and secure AI models, applying advanced defense mechanisms like adversarial training and differential privacy. You’ll be equipped to assess vulnerabilities, implement robust security strategies, and continuously test and improve your models. With hands-on experience fixing real-world AI vulnerabilities, you'll be prepared to design and deploy AI systems that are resilient against adversarial threats, ensuring their integrity and security throughout their lifecycle.

Навыки, которые вы освоите

AI SecurityGenerative Adversarial Networks (GANs)Security TestingSecurity Architecture ReviewIT Security ArchitectureThreat ModelingModel TrainingData ValidationSecurity Requirements AnalysisInformation PrivacyDesignVulnerability AssessmentsAnalysisSecurity ControlsModel EvaluationHardeningSecurity StrategyData IntegrityContinuous MonitoringSecurity Engineering

Программа курса

3 модулей · 23 учебных материалов

01The Attacker's Playbook: Understanding AI Vulnerabilities8 материалов
The Trojan Horse in the CodeDIALOGUEWelcome to the Course: Course OverviewЧтениеWelcome to Advanced AI Security: Interpret & DefendВидеоEvasion Attacks: Fooling the Model's SensesВидео

Учитесь у экспертов

Starweaver

Global Leaders in Professional & Technology Education

Rifat Erdem Sahin

AI Solutions Architect | Agent & LLM Specialist | CI/CD Automation Engineer | DevOps Contracts | Security-Cleared Professional

Secure AI Interpret and Protect Models
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Обучение на Coursera

≈ 5.6 ч

3 модулей

Язык: Английский

Часть программы вашего университета
Data Poisoning: Corrupting Intelligence from WithinВидео
Model Stealing and Extraction: The Digital HeistВидео
Hands-On-Learning: Exploiting AI VulnerabilitiesВзаимная проверка
Attacking Machine Learning with Adversarial ExamplesЧтение
02Building the Shield: Proactive Defense Strategies6 материалов
The Pre-Mortem: Fortifying a New AI SystemDIALOGUEAdversarial Training: Fighting Fire with Fire and build your foundationsВидеоInput Sanitization: Your First Line of DefenseВидеоDifferential Privacy: Protecting Data, Preserving InsightВидеоHands-On-Learning: Implementing Defense Mechanisms for ML Security Взаимная проверкаExplaining and Harnessing Adversarial ExamplesЧтение
03Adversarial Testing and the Continuous Cycle9 материалов
Zero-Day Defiance: The Live-Fire ExerciseDIALOGUEStress Testing Your Model: Designing Adversarial Evaluations for Red TeamsВидеоInterpreting Results: Measuring Resilience and Finding Weak SpotsВидеоThe Full Circle: Implementing the AI Security LifecycleВидеоHands-On-Learning: ML Security Operations and Red TeamingВзаимная проверкаMicrosoft’s AI Red Team is Building a Safer Future for AIЧтениеCourse Wrap-UpВидеоProject: SynthSafe: The Final Security Audit Взаимная проверкаSecure AI Interpret and Protect ModelsЗадание