AI Security

Master the art and science of securing AI and machine learning systems. From adversarial attacks and prompt injection to governance frameworks and zero trust architectures — learn to protect AI systems at every layer.

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20 Courses

140 Lessons

100% Free

All Courses

20 comprehensive courses covering every aspect of AI and ML security.

Core Security

AI Security Fundamentals

Build a solid foundation in AI security principles, threat landscapes, and defense strategies for machine learning systems.

Model Security & Protection

Protect ML models from theft, extraction, and inversion attacks with encryption, watermarking, and access controls.

AI Threat Modeling

Apply structured threat modeling methodologies like STRIDE to AI and ML systems for proactive security.

Model Watermarking & IP Protection

Protect intellectual property in ML models with watermarking, fingerprinting, and legal frameworks.

Attack & Defense

Adversarial Attacks & Defenses

Understand adversarial machine learning attacks including FGSM, PGD, and black-box methods, plus proven defense techniques.

LLM Security & Prompt Injection

Protect large language models from prompt injection, jailbreaking, and data exfiltration attacks.

Deepfake Detection

Detect AI-generated synthetic media including image, video, and audio deepfakes using modern detection techniques.

Privacy & Compliance

Data Privacy for AI Systems

Implement data privacy protections for AI systems including GDPR compliance, anonymization, and privacy-preserving ML.

AI Governance & Compliance

Navigate AI regulations including the EU AI Act and NIST AI RMF, and build effective governance programs.

Differential Privacy for ML

Apply differential privacy to machine learning with DP-SGD, privacy budgets, and practical implementation patterns.

Applied Security

Secure ML Pipelines

Build end-to-end secure machine learning pipelines from data ingestion to deployment with proper security controls.

Federated Learning Security

Secure federated learning systems against Byzantine attacks with secure aggregation and differential privacy.

AI Supply Chain Security

Manage risks in the AI supply chain including pre-trained models, datasets, and dependency vulnerabilities.

AI-Powered Cybersecurity

Leverage AI and ML for cybersecurity including intrusion detection, malware analysis, and automated threat response.

Securing AI APIs

Protect AI-powered APIs with authentication, rate limiting, input validation, and comprehensive monitoring.

Secure Data Labeling

Implement security controls for data labeling workflows including PII protection, access controls, and audit trails.

Security Operations

AI Red Teaming

Plan and execute AI red team exercises to test model robustness, safety, and security before deployment.

AI Incident Response

Prepare for and respond to AI security incidents with detection, triage, containment, and recovery procedures.

Zero Trust for AI Systems

Apply zero trust architecture principles to AI workloads with identity, micro-segmentation, and continuous verification.

AI Security Auditing

Conduct comprehensive AI security audits covering technical assessment, data security, and compliance verification.

What You'll Learn

Skills you will gain across these 20 AI security courses.

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Threat Analysis

Identify and model threats to AI systems including adversarial attacks, data poisoning, model extraction, and prompt injection vulnerabilities.

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Defense Implementation

Build robust defenses with adversarial training, input sanitization, output filtering, differential privacy, and secure ML pipelines.

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Governance & Compliance

Navigate AI regulations like the EU AI Act and NIST AI RMF. Build governance programs with audit practices and compliance automation.

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Security Operations

Conduct red team exercises, respond to AI incidents, perform security audits, and implement zero trust architectures for AI workloads.