Differential Privacy Codelab in Python/PipelineDP on Oct 26/27
DP Open Source Users
Hi all,
We are facilitating another codelab for computing private statistics with differential privacy in Python (using PipelineDP). Come join us if you're interested and feel free to spread the word amongst interested audiences!
Logistics: Remotely facilitated via Meet
Register via: https://rsvp.withgoogle.com/events/gsec-data-anonymization-codelab
Date & time:
Wednesday 26th October 2022 (6:00 - 6:50 pm, CET) EMEA/Americas friendly
Thursday 27th October 2022 (10:00 - 10:50 am, CET) EMEA/APAC friendly
Facilitators:
Mirac Vuslat Basaran, Software Engineer
Mirac is a Software Engineer in the area of anonymization and differential privacy at Google. Before joining Google, he studied Computer Engineering (and Economics) at Bilkent University. Currently, he helps build and open source infrastructure for product teams to anonymize their data. He also consults product teams on anonymization and differential privacy.
Niels Overwijn, Privacy Solutions Engineer
Niels is a privacy focussed Customer Solutions Engineer, building custom solutions and providing technical consultations to help the largest customers and agencies across Northern Europe.
Targeted audience: This codelab is geared towards startup developers, data scientists, business analysts, and product managers who work with or analyze personable identifiable datasets. This is also a great program for software developers, data scientists, and data analysts who hope to improve their product offerings or plan to publish statistics based on datasets that require a robust data anonymization technique to protect their user’s privacy and prevent data leakages.
Experience requirements: Participants need to be able to read and write Python, the open source programming language, to follow the codelab and understand the computational models.
Pre-work: Before the codelab, we recommend reading up on the topics of data anonymization and differential privacy. You should read the Python introduction to familiarize yourself with a high-level library for writing data-processing pipelines. You’ll want to have this page ready if you want to code along during the introduction of the codelab. Learn more about PipelineDP and how to get started here.
Thanks,