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Learn Data Privacy, earn certificates with paid and free online courses from Harvard, Stanford, UC Irvine, Yale and other top universities around the world. Read reviews to decide if a class is right for you.
Gain a clear understanding of data privacy principles and how to implement privacy and security processes.
2021 CIPT CIPM CIPP/E - Examples of how a GDPR Privacy professional should approach GDPR data protection compliance
Comprehensive exploration of data privacy principles, protection standards, and implementation strategies. Covers key regulations, security measures, and ethical considerations for effective data management.
Master ethical principles of biomedical data management, covering privacy, security, and sharing practices while exploring historical context and modern challenges in research data handling.
Explore the impact of differential privacy on Census data, focusing on redistricting implications and the balance between data protection and accuracy in demographic statistics.
Explores the implications of the Google Spain decision on data privacy, dignitary privacy, and freedom of expression in the digital age, examining the balance between privacy rights and public discourse.
Get an introduction to the basics of data privacy: what it is, why it matters, and who it impacts, from consumers and private citizens to policymakers and C-suite business leaders.
Examine definitions, components, and business applications of the California Consumer Privacy Act (CCPA). Learn about the regulations required and explore GDPR similarities.
Balance growth with trust. Learn how to share data with appropriate privacy controls, including how to use k-anonymity and l-diversity to protect your users' information.
Follow an expert in data analytics to learn how to best protect your privacy online.
Explore Facebook's Startup Garage initiative and discover how data startups are innovating in the privacy ecosystem, with key insights and lessons learned.
Explore a novel technique for detecting dataset usage in model training through imperceptible "radioactive" data markers, offering robust identification even with minimal data exposure.
Explore ethical challenges in algorithmic design, focusing on data privacy and fairness. Learn about differential privacy, anonymization techniques, and defining fairness in AI systems.
Explore data privacy techniques for Apache Spark, including offensive and defensive approaches, k-anonymity, and quasi-identifiers. Learn implementation strategies and how Databricks Delta enhances dataset privacy.
Learn strategies for scaling privacy in Spark ecosystems, balancing customer rights with business needs. Explore centralized access control, auditing, and reporting in open data environments.
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