CM
This course provides practical steps to protect privacy.

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.

CM
This course provides practical steps to protect privacy.
BS
This was a very interesting eye opening Course of the Future, thank you.
SY
A relatively short but interesting course relating to privacy concerns around AI and ways to manage/improve models to address these concerns.
YL
The concepts were easier to grasp and a nice introduction into the complexities around algorithmic models and building ethical practices from the outset.
CA
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
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This was a very interesting eye opening Course of the Future, thank you.
The course was quite good and provided further insight into ethics and AI modeling, providing new perspectives for both professionals and non-professionals.
A relatively short but interesting course relating to privacy concerns around AI and ways to manage/improve models to address these concerns.
Extraordinary course! I've really enjoyed it and learned so much. Classes are very clear and concise. Thank you so much!
Simple but realy effective ! Keep doing great stuff at learnQuest
This course provides practical steps to protect privacy.
This course was very interesting
really Great And Accessible
more courses are required
شكرا stc شكرا coursera .
Very good
10/10
good
good
yey
no
Some aspects of privacy and explainability are covered in this course. It can go little more deeper with few more use cases so that the learners can relate to real world applications of privacy. Can we really compromise accuracy at the cost of privacy in real world?
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
The concepts were easier to grasp and a nice introduction into the complexities around algorithmic models and building ethical practices from the outset.
Some interesting info but : _ not dense enough (Too easy) _ frequently too vague and even inacurate. - teacher voice (is it synthetic ?) is painful to hear