Adversarial Machine Learning with CSV and Image Data

Udemy MOOC / Non-credit USD 59.99

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Adversarial Machine Learning with CSV and Image Data

About this course

In this course, you'll explore the intricate world of Adversarial Machine Learning (AML), focusing on how to both attack and defend AI models. It covers various types of adversarial attacks and provides hands-on experience simulating these attacks with CSV and image data. Along the way, you'll delve into strategies for building a strong defense, including the use of Generative Adversarial Networks (GANs) and the ethical implications of these techniques.

What you'll learn

understand different types of adversarial attacks
simulate adversarial attacks on machine learning models
implement defenses against adversarial attacks
apply techniques involving Generative Adversarial Networks (GANs)
evaluate the ethical considerations in using AML strategies

Course objectives

to teach advanced techniques in adversarial machine learning
to equip students with practical skills in AI security
to foster understanding of ethical issues in AI

Skills you'll gain

model evaluation ai security cybersecurity ethical considerations adversarial machine learning adversarial attacks image data generative adversarial networks csv data machine learning defenses

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