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Course Description

Although traditional data privacy protection methods such as aggregation, suppression, and swapping offer a layer of protection for your data, they do not provide a theoretical guarantee of data protection. Instead, techniques using differential privacy employ a mathematical definition of privacy to limit the amount of additional information disclosed for any individual. In this lesson, you will discover the role that differential privacy has in ensuring your customers know and believe your brand keeps their data safe. You will also delve into future considerations and challenges of data privacy measures as well as the impact those measures may have on your brand positioning.

Benefits to the Learner

  • Explore differential privacy
  • Understand privacy as a competitive advantage
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Type
self-paced (non-instructor led)
Dates
Feb 23, 2021 to Dec 31, 2030
Total Number of Hours
1.0
Course Fee(s)
Regular Price $0.00
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