In this course, we will explore fundamental concepts involved in security and privacy of machine learning projects. Diving into the ethics behind these decisions, we will explore how to protect users from privacy violations while creating useful predictive models. We will also ask big questions about how businesses implement algorithms and how that affects user privacy and transparency now and in the future.
This course is part of the Ethics in the Age of AI Specialization
About this Course
Skills you will gain
- Machine Learning
- Ethics Of Artificial Intelligence
Syllabus - What you will learn from this course
Privacy and convenience vs big data
Protecting Privacy: Theories and Methods
Building Transparent Models
- 5 stars70%
- 4 stars26%
- 3 stars4%
TOP REVIEWS FROM ARTIFICIAL INTELLIGENCE PRIVACY AND CONVENIENCE
The concepts were easier to grasp and a nice introduction into the complexities around algorithmic models and building ethical practices from the outset.
A relatively short but interesting course relating to privacy concerns around AI and ways to manage/improve models to address these concerns.
This course provides practical steps to protect privacy.
A good course on balancing between privacy and aggregate results. It tells how anonymization should be done. It did not cover enough the correlations between privacy and accuracy though
About the Ethics in the Age of AI Specialization
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