Homomorphic and privacy encryption course in AI models
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Syllabus
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Summary
In the current era, where data is new oil and artificial intelligence (AI) drives innovation, the privacy of data has become a critical concern. The growing adoption of AI models in the cloud and with sensitive data underlines the need for technologies that allow processing without exposing the original information. Homomorphic encryption emerges as a revolutionary solution, allowing calculations directly on encrypted data without deciphering them. The homomorphic and privacy encryption course in AI models addresses the demand of experts, capable of implementing AI solutions that guarantee privacy, crucial in sectors such as health or finance.
Goals
Professional opportunities
To prepare you
When completing the homomorphic and privacy encryption course in AI models, students will be able to design and implement AI models that operate on encrypted data, guaranteeing privacy and information security. Skills will be acquired to select the appropriate homomorphic encryption scheme, integrate it into working flows of Machine Learning and evaluate its performance and safety.
Who is it addressed to?
The homomorphic encryption and privacy course in AI models is aimed at Machine Learning professionals, data science, research in AI, cybersecurity, software development and privacy, with interest in data protection in artificial intelligence environments. It is ideal for those who seek to deepen homomorphic encryption techniques and their application.
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