Course Details
Country:
Netherlands
Institution:
Free University of Amsterdam
Course Title:
Differential Privacy and Statistical Inference under Differential Privacy
Course Number:
E_EOR3_DP
Course Description:
Access to data is key for scientific progress. Yet, data is often sensitive in nature and must, therefore, fulfil certain requirements to ensure privacy. For instance, publicly available data should be arranged such that nobody can trace back the individuals in the dataset. In this course, you will learn about a solid mathematical framework called Differential Privacy (DP), that enables you to quantify the loss in privacy by releasing data or results into the public domain. Moreover, you will learn about algorithms that actually give you control over the amount of privacy that is lost by such a release. These algorithms, in essence, simply add some noise to the data. Intuitively, it should be clear that such perturbations will affect parameter estimates and their uncertainty (e.g., when estimating the effect of years of schooling on income later in life).
Language:
English
Approved Equivalent:
Pending For Approval
Attachment Files:
Studyguide (15)_8.pdf
