AI Security & Adversarial ML Courses

Adversarial ML studies how attackers can manipulate AI systems through crafted inputs, data poisoning, or model extraction. Understanding these threats is essential for building secure AI applications.

Prompt injection is an attack where malicious input manipulates an LLM into ignoring its instructions or leaking sensitive information. Defending against it is a critical concern for LLM-powered applications.

Techniques include adversarial training, input validation, output filtering, model ensembling, and continuous red-teaming. Defense-in-depth strategies combining multiple approaches offer the strongest protection.

Yes, AI security is a rapidly growing field. Organizations need specialists who understand both ML and cybersecurity. Roles include AI red teamer, ML security engineer, and AI safety researcher.