Privacy-preserving AI

Overview

Privacy is a paramount concern in the realm of AI systems, where vast amounts of sensitive data are processed regularly. Inadequate attention to privacy risks can result in regulatory penalties, diminished trust, and lost opportunities for innovation.

The course "Privacy-preserving AI" empowers you to implement Privacy-enhancing Technologies (PETs) effectively, striking a critical balance between data utility, privacy, and compliance.

Initially, delve into the core techniques of privacy-preserving AI, such as Differential Privacy, Federated Learning, and Homomorphic Encryption. Progress to learn practical implementation of these technologies within AI workflows, ensuring adherence to regulations like GDPR without sacrificing performance.

Conclude your learning journey by tackling the challenges posed by privacy-preserving AI, including computational overhead and trade-offs in data utility, while committing to ethical AI principles.

By course completion, you'll possess the expertise required to develop secure, compliant, and trustworthy AI systems that not only foster innovation but also maintain user confidence. Join Pluralsight to acquire essential skills in a range of subjects, including Artificial Intelligence, GDPR, Federated Learning, Data Privacy, and Data Protection courses.

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