Drew Data Protection & Cybersecurity Academy - Singapore Data Festival Webinar Series #3: Differential Privacy in Machine Learning
Differential Privacy (DP) is commonly cited as a powerful Privacy Enhancing Technology (PET) that provides mathematical privacy guarantees to protect and secure private or personal data. Due to growing concerns – including actual attacks aimed at soliciting or extracting personal data from AI models – various forms of DP have been proposed to provide or achieve a sufficient level of anonymisation during the Machine Learning (ML) stage of AI model development.
In our third webinar of the SDF series, you will learn about the core concepts of how DP has been applied to ML, without getting bogged down in overly complex technical or mathematical explanations, while gaining more practical clarity beyond the typical “just add noise to the data”.
| Date: |
Wednesday, 22 July 2026 |
| Time: | 12.00pm - 1.00pm (SGT) |
| Speaker: | Albert Pichlmaier |
Upon successful registration, you will receive a confirmation email with details of how to access the webinar.
If you have not received the log-in details by the morning of 22 July 2026, and if the log-in details have not been received in your spam / junk mailbox, kindly contact Ms Natalie Wong at
natalie.wong@drewnapier.com for further assistance.
