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Securing AI and Advanced Topics · LearnSpace
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courseraIT и технологии

Securing AI and Advanced Topics

Курс от Johns Hopkins University
Средний≈ 15.5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

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.

Навыки, которые вы освоите

AI SecurityReinforcement LearningGenerative Adversarial Networks (GANs)Model EvaluationFraud detectionFeature EngineeringCyber Security StrategyData SynthesisModel OptimizationCybersecurity

Программа курса

6 модулей · 43 учебных материалов

01Course Introduction2 материалов
Course OverviewЧтениеInstructor Biography - Lanier WatkinsЧтение
02Fraud Prevention with Cloud AI Solutions8 материалов

Credit Card Fraud Threats and AI Prevention

Credit Card Fraud Prevention with AIВидео

Учитесь у экспертов

Lanier Watkins

Преподаватель курса

Securing AI and Advanced Topics
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 15.5 ч

6 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский, Казахский, Венгерский

Часть программы вашего университета
Reading ReferencesЧтение
Credit Card Fraud Threats and AI PreventionЗадание

Implementing and Evaluating IBM Watson for Fraud Detection

Credit Card Fraud Prevention: IBM Watson ExampleВидеоReading ReferencesЧтениеImplementing and Evaluating IBM Watson for Fraud DetectionЗадание

Module-end Assessments

Self-Reflective Reading: Understanding of AI Fraud Prevention ToolsЧтениеFraud Prevention with Cloud AI SolutionsЗадание
03 Introduction to Generative Adversarial Attacks (GANs)8 материалов

Fundamentals of Generative Adversarial Networks (GANs)

Introduction to Generative Adversarial Networks (GANs)ВидеоReading ReferencesЧтениеFundamentals of Generative Adversarial Networks (GANs)Задание

Hands-On GAN Implementation and Synthetic Data Generation

Getting to Know GANsВидеоReading ReferencesЧтениеHands-On GAN Implementation and Synthetic Data GenerationЗадание

Module-end Assessments

Self-Reflective Reading: Research GANsЧтениеIntroduction to Generative Adversarial Attacks (GANs)Задание
04GANs and Adversarial Attacks9 материалов

Understanding Black-box and White-box Adversarial Attacks

Adversarial Attacks ExplainedВидеоReading ReferencesЧтениеUnderstanding Black-box and White-box Adversarial AttacksЗадание

Practical Implementation of Adversarial Attacks

Hands-On Adversarial AttacksВидеоReading ReferencesЧтениеPractical Implementation of Adversarial AttacksЗадание

Module-end Assessments

Self-Reflective Reading: GANs and Adversarial AttacksЧтениеPractice Lab: Generating Synthetic QR Codes with the Trained GeneratorЛабораторнаяGANs and Adversarial AttacksЗадание
05Reinforcement Learning8 материалов

Reinforcement Learning and Its Applications

Reinforcement LearningВидеоReading ReferencesЧтениеReinforcement Learning and its ApplicationsЗадание

Using RL for Adversarial Attacks and Optimizing Datasets

Evading Malware Detectors with RLВидеоReading ReferencesЧтениеUsing RL for Adversarial Attacks and Optimizing DatasetsЗадание

Module-end Assessments

Self-Reflective Reading: Understanding Reinforcement LearningЧтениеReinforcement LearningЗадание
06Evaluating AI Models and Performance8 материалов

Feature Engineering and Model Optimization Techniques

Challenges with Using AI for CybersecurityВидеоReading ReferencesЧтениеFeature Engineering and Model Optimization TechniquesЗадание

Evaluating AI Models and Performance Metrics

Evaluating AI ModelsВидеоReading ReferencesЧтениеEvaluating AI Models and Performance MetricsЗадание

Module-end Assessments

Self-Reflective Reading: Feature Engineering in Cybersecurity ApplicationsЧтениеEvaluating AI Models and PerformanceЗадание