Edge AI Security and Privacy in AI at the Edge focuses on protecting data, models, and devices in edge computing environments. Edge AI runs data locally on devices such as sensors, mobile systems, and IoT devices. This reduces latency but introduces new security risks. This training explains key concepts like data encryption, secure model deployment, and privacy-preserving techniques. It also covers threat detection at the edge, authentication, access control, and federated learning. You will learn how organizations secure AI systems in distributed environments. The course also highlights best practices for building resilient and privacy-aware edge AI solutions.
