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Starts 4 July 2025 16:46
Ends 4 July 2025
Privacy for AI from NP-Hard Problems - Universal Compute on Encrypted Data
Open Compute Project
2777 Courses
15 minutes
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Overview
Join this insightful course on cryptographic methods crucial for safeguarding privacy in AI applications. Delve into the intricacies of MultiParty Computation, Threshold Cryptography, and Fully Homomorphic Encryption.
This course gives particular attention to overcoming challenges in evaluating complex operations like softmax while maintaining data encryption.
Presented by esteemed instructors on YouTube, this course is a vital part of both Artificial Intelligence and Computer Science disciplines, offering an in-depth understanding of universal compute on encrypted data. Ideal for those looking to advance their knowledge in state-of-the-art cryptographic techniques within AI frameworks.
Syllabus
- Introduction to Privacy in AI
- Cryptographic Foundations
- MultiParty Computation (MPC)
- Threshold Cryptography
- Fully Homomorphic Encryption (FHE)
- Privacy-preserving AI Operations
- Designing Privacy-preserving AI Systems
- Advanced Topics and Emerging Trends
- Conclusion and Future Directions
- Final Project or Assessment
Subjects
Computer Science