Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Online Course

Artificial Intelligence Privacy and Convenience

LearnQuest via Coursera

Overview

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.

Syllabus

Privacy and convenience vs big data
-In Module 1, we are going to discuss what true anonymity and privacy mean in machine learning

Protecting Privacy: Theories and Methods
-In Module 2, we are going to take a deeper look at dataset security. We will also look into methods to add privacy to existing and new datasets to protect those individuals in them

Building Transparent Models
-In Module 3, we will discuss putting ethical, private models into practice. We will explore the explainable AI movement as well as tradeoffs for the teams putting together these algorithms

Taught by

Sabrina Moore and Brent Summers

Related Courses

Reviews

0.0 rating, based on 0 reviews

Start your review of Artificial Intelligence Privacy and Convenience

Never stop learning Never Stop Learning!

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free