CYBERSECURITY AND PRIVACY FOR ARTIFICIAL INTELLIGENCE

Catalog description

Foundations of securing artificial intelligence and machine learning systems across the AI lifecycle. Topics include vulnerabilities in AI pipelines such as data poisoning, adversarial and privacy attacks, model extraction and inference risks, threats to generative AI and large language models, privacy-preserving learning, secure MLOps, and AI risk management and governance.