Explore differential privacy

Data Scientist
Machine Learning

Data scientists have an ethical (and often legal) responsibility to protect sensitive data. Differential privacy is a leading edge approach that enables useful analysis while protecting individually identifiable data values.

Learning objectives

After completing this module, you'll be able to:

  • Articulate the problem of data privacy
  • Describe how differential privacy works
  • Configure parameters for differential privacy
  • Perform differentially private data analysis


  • Knowledge of Python
  • Experience of training models using the Azure Machine Learning SDK