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Securing AI and Advanced Topics

Securing AI and Advanced Topics

本课程是 AI for Cybersecurity 专项课程的一部分

位教师：Lanier Watkins

2,591 人已注册

包含在中

了解更多

6个模块

深入了解一个主题并学习基础知识。

25 条评论

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

6个模块

深入了解一个主题并学习基础知识。

25 条评论

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Learn to implement AI-based solutions to detect and prevent credit card fraud in cloud environments.
Explore the fundamentals of Generative Adversarial Networks and their applications in generating synthetic data.
Gain hands-on experience with black-box and white-box adversarial attacks to assess and enhance model resilience.
Master techniques in feature engineering and performance evaluation to optimize AI models for cybersecurity applications.

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

15 项作业

授课语言：英语（English）

91%

of learners achieved a positive career outcome

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 AI for Cybersecurity 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有6个模块

In the course "Securing AI and Advanced Topics", learners will delve into the cutting-edge intersection of AI and cybersecurity, focusing on how advanced techniques can secure AI systems against emerging threats. Through a structured approach, you will explore practical applications, including fraud prevention using cloud AI solutions and the intricacies of Generative Adversarial Networks (GANs). Each module builds upon the previous one, enabling a comprehensive understanding of both offensive and defensive strategies in cybersecurity.

What sets this course apart is its hands-on experience with real-world implementations, allowing you to design effective solutions for detecting and mitigating fraud, as well as understanding adversarial attacks. By evaluating AI models and learning reinforcement learning principles, you will gain insights into enhancing cybersecurity measures. Completing this course will equip you with the skills necessary to address complex challenges in the evolving landscape of AI and cybersecurity, making you a valuable asset in any organization. Whether you are seeking to deepen your expertise or enter this critical field, this course provides the tools and knowledge you need to excel.

单元详情

This course provides a comprehensive exploration of AI-based solutions for credit card fraud detection, emphasizing the implementation and evaluation of advanced algorithms, including Generative Adversarial Networks (GANs). Students will gain practical experience in executing adversarial attacks and optimizing machine learning models, enhancing their ability to develop robust AI systems. Through hands-on projects, participants will synthesize knowledge to address real-world challenges in fraud detection and model resilience.

涵盖的内容

2篇阅读材料

In this module, we study the background of threats that prevent credit card fraud. Then, we investigate hands-on credit card fraud detection implementations. Also, we discuss metrics to evaluate the performance of credit card fraud detection algorithms.

涵盖的内容

2个视频3篇阅读材料3个作业

2个视频总计14分钟

Credit Card Fraud Prevention with AI4分钟
Credit Card Fraud Prevention: IBM Watson Example10分钟

3篇阅读材料总计65分钟

Reading References10分钟
Reading References10分钟
Self-Reflective Reading: Understanding of AI Fraud Prevention Tools45分钟

3个作业总计90分钟

Credit Card Fraud Threats and AI Prevention15分钟
Implementing and Evaluating IBM Watson for Fraud Detection15分钟
Fraud Prevention with Cloud AI Solutions60分钟

In this module, we study generative adversarial networks (GANs) background. Then, we investigate a hands-on GAN implementation and how it can be used to develop synthetic data likely indistinguishable from the real data.

涵盖的内容

2个视频3篇阅读材料3个作业

2个视频总计17分钟

Introduction to Generative Adversarial Networks (GANs)9分钟
Getting to Know GANs8分钟

3篇阅读材料总计70分钟

Reading References15分钟
Reading References10分钟
Self-Reflective Reading: Research GANs45分钟

3个作业总计90分钟

Fundamentals of Generative Adversarial Networks (GANs)15分钟
Hands-On GAN Implementation and Synthetic Data Generation15分钟
Introduction to Generative Adversarial Attacks (GANs)60分钟

In this module, we will discuss black and white-box adversarial attacks. Also, we will explore hands-on implementations of several adversarial attacks.

涵盖的内容

2个视频3篇阅读材料3个作业1个非评分实验室

2个视频总计18分钟

Adversarial Attacks Explained8分钟
Hands-On Adversarial Attacks9分钟

3篇阅读材料总计65分钟

Reading References10分钟
Reading References10分钟
Self-Reflective Reading: GANs and Adversarial Attacks45分钟

3个作业总计90分钟

Understanding Black-box and White-box Adversarial Attacks15分钟
Practical Implementation of Adversarial Attacks15分钟
GANs and Adversarial Attacks60分钟

1个非评分实验室总计60分钟

Practice Lab: Generating Synthetic QR Codes with the Trained Generator60分钟

In this module we will study reinforcement learning (RL) and how it can be used for adversarial attacks. Also, we will study data engineering techniques to optimize datasets to help improve ML model performance.

涵盖的内容

2个视频3篇阅读材料3个作业

2个视频总计14分钟

Reinforcement Learning8分钟
Evading Malware Detectors with RL6分钟

3篇阅读材料总计65分钟

Reading References10分钟
Reading References10分钟
Self-Reflective Reading: Understanding Reinforcement Learning45分钟

3个作业总计90分钟

Reinforcement Learning and its Applications15分钟
Using RL for Adversarial Attacks and Optimizing Datasets15分钟
Reinforcement Learning60分钟

In this module, we will discuss feature engineering and model optimization techniques. Also, we will explore ML model performance metrics.

涵盖的内容

2个视频3篇阅读材料3个作业

2个视频总计17分钟

Challenges with Using AI for Cybersecurity9分钟
Evaluating AI Models8分钟

3篇阅读材料总计65分钟

Reading References10分钟
Reading References10分钟
Self-Reflective Reading: Feature Engineering in Cybersecurity Applications45分钟

3个作业总计90分钟

Feature Engineering and Model Optimization Techniques15分钟
Evaluating AI Models and Performance Metrics15分钟
Evaluating AI Models and Performance60分钟

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

授课教师评分

(6个评价)

Lanier Watkins

Johns Hopkins University

3 门课程11,400 名学生

提供方

Johns Hopkins University

Securing AI and Advanced Topics

Securing AI and Advanced Topics

您将学到什么

您将获得的技能

您将学习的工具

要了解的详细信息

了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识

该课程共有6个模块

Course Introduction

涵盖的内容

Fraud Prevention with Cloud AI Solutions

涵盖的内容

Introduction to Generative Adversarial Attacks (GANs)

涵盖的内容

GANs and Adversarial Attacks

涵盖的内容

Reinforcement Learning

涵盖的内容

Evaluating AI Models and Performance

涵盖的内容

获得职业证书

位教师

提供方

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常见问题

When will I have access to the lectures and assignments?

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Is financial aid available?

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