Overview
Context
Data privacy has never been more important. But how do you balance privacy with the need to gather and share valuable business insights?
In this Data Privacy and Anonymization in Python course offered by Data Camp, you'll learn how to do just that, using the same methods as Google and Amazon—including data generalization and privacy models, like k-Anonymity and differential privacy.
In addition to touching on topics such as GDPR, you'll also discover how to build and train machine learning models in Python while protecting employee and income data. Let’s get started!
Programme Structure
Chapters
- More on Privacy-Preserving Techniques
- Differential Privacy
- Anonymizing and Releasing Datasets
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Campus Location
- New York City, United States
Disciplines
Software Engineering Machine Learning View 207 other Short Courses in Machine Learning in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- This course is targeted at Advanced learners.
- This course covers essential data privacy concepts and is beneficial for those who work in fields such as data science, artificial intelligence, data analysis, software engineering, and more, who need to ensure the privacy and security of their data and users' data.
PREREQUISITES
- Unsupervised Learning in Python
Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
This course can be accessed for free with the Data Camp Premium or Teams subscriptions