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
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Offered By
Ethics in the Age of AI SpecializationLearnQuestAbout this Course
Flexible deadlines
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Shareable Certificate
Earn a Certificate upon completion
100% online
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Course 3 of 4 in the
Intermediate Level
Approx. 6 hours to complete
English
Subtitles: French, Portuguese (European), Russian, English, Spanish
Skills you will gain
- Ethics
- Machine Learning
- Ethics Of Artificial Intelligence
- security
- Privacy
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 3 of 4 in the
Intermediate Level
Approx. 6 hours to complete
English
Subtitles: French, Portuguese (European), Russian, English, Spanish
Offered by
LearnQuest
LearnQuest is the preferred training partner to the world’s leading companies, organizations, and government agencies. Our team boasts 20+ years of experience designing, developing and delivering a full suite industry-leading technology education classes and training solutions across the globe. Our trainers, equipped with expert industry experience and an unparalleled commitment to quality, facilitate classes that are offered in various delivery formats so our clients can obtain the training they need when and where they need it.
Syllabus - What you will learn from this course
2 hours to complete
Privacy and convenience vs big data
In Module 1, we are going to discuss what true anonymity and privacy mean in machine learning
2 hours to complete
5 videos (Total 19 min), 2 readings, 3 quizzes
2 hours to complete
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
2 hours to complete
4 videos (Total 16 min), 2 readings, 3 quizzes
2 hours to complete
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
2 hours to complete
5 videos (Total 20 min), 1 reading, 3 quizzes
Reviews
- 5 stars68.88%
- 4 stars26.66%
- 3 stars4.44%
TOP REVIEWS FROM ARTIFICIAL INTELLIGENCE PRIVACY AND CONVENIENCE
by SYApr 2, 2021
A relatively short but interesting course relating to privacy concerns around AI and ways to manage/improve models to address these concerns.
by YLMay 22, 2021
The concepts were easier to grasp and a nice introduction into the complexities around algorithmic models and building ethical practices from the outset.
by AVJan 16, 2021
Extraordinary course! I've really enjoyed it and learned so much. Classes are very clear and concise. Thank you so much!
by BTDec 22, 2020
This was a very interesting eye opening Course of the Future, thank you.
About the Ethics in the Age of AI Specialization
As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations. In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in security and privacy of machine learning projects. We'll finish with a study of 3 projects that will allow you to put your new skills into action.
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