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Generative AI for Cybersecurity Professionals · LearnSpace
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courseraПрограммирование

Generative AI for Cybersecurity Professionals

Курс от Edureka
Средний≈ 12.2 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This program equips cybersecurity professionals, AI security practitioners, SOC leaders, and governance specialists with the expertise required to integrate Artificial Intelligence and Generative AI into security operations responsibly and securely. You will begin by exploring AI fundamentals, comparing traditional detection approaches with AI-driven analytics, and understanding how Large Language Models enhance SOC workflows. Through guided demonstrations, you will examine real-world applications such as AI-based malware detection, automated triage, and intelligent threat analysis. Building on AI foundations, you will explore transformer architectures, evaluate LLM capabilities and limitations, and apply AI systems to cybersecurity use cases. Emphasis is placed on identifying output risks, implementing guardrails, and maintaining human oversight in AI-assisted workflows. Next, the program advances into secure prompt engineering and AI system defense. You will learn how prompt injection attacks occur, how adversarial machine learning manipulates models, and how AI pipelines can be hardened against misuse. Structured exercises demonstrate how robust model training, monitoring, and validation reduce AI-specific security risks. The course then expands into governance, ethics, and compliance frameworks. You will analyze bias, fairness, transparency, and accountability challenges in AI systems, and align AI deployment with recognized standards such as NIST and regulatory compliance frameworks. Practical examples demonstrate how to audit AI systems and establish responsible oversight mechanisms. Finally, you will integrate AI security, adversarial defense, and governance strategies in a structured practice project, designing a secure AI-enabled SOC framework aligned with enterprise risk management principles. By the end of this program, you will be able to: -Explain AI, GenAI, and LLM concepts in cybersecurity contexts. -Apply AI and LLMs to enhance SOC detection and triage workflows. -Design secure prompt engineering and guardrail controls. -Identify vulnerabilities across AI pipelines and system architectures. -Defend against adversarial machine learning attacks. -Implement ethical, transparent, and compliant AI governance frameworks. -Audit AI-assisted decisions for bias, risk, and misuse. -Design a secure AI-driven security operations strategy. This course is designed for SOC professionals, cybersecurity engineers, AI security practitioners, governance officers, and security leaders seeking to responsibly integrate AI into enterprise defense strategies. Join us to build the technical insight, defensive resilience, and governance expertise required to secure AI-powered cybersecurity operations in modern enterprises.

Навыки, которые вы освоите

AI SecurityGenerative AIPrompt EngineeringLarge Language ModelingLLM ApplicationResponsible AIGenerative Model ArchitecturesData EthicsAI IntegrationsAutomationCyber Security PoliciesCyber RiskRiskingArtificial Intelligence and Machine Learning (AI/ML)CybersecuritySecurity AwarenessMachine LearningCyber Security StrategyCyber AttacksCyber Threat Intelligence

Программа курса

3 модулей · 86 учебных материалов

01Artificial Intelligence and Large Language Models in Cybersecurity28 материалов

Leveraging AI, Generative AI, and LLMs in Cybersecurity

Specialization IntroductionВидеоCourse IntroductionВидеоCourse OverviewЧтениеWhat Do You Know About AI-Driven Security and Responsible AI Governance?DIALOGUE

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Edureka

Преподаватель курса

Generative AI for Cybersecurity Professionals
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Обучение на Coursera

≈ 12.2 ч

3 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Испанский, Японский

Часть программы вашего университета
Introducing AI in CybersecurityВидео
Comparing Traditional Security and AI-Driven DetectionВидео
Exploring the Real-world Applications of AI in Cyber DefenseВидео
Introduction to Generative AI SystemsВидео
Modeling Core Generative AI SystemsВидео
Analyzing Key Generative AI Models (GANs, VAEs, LLMs)Видео
Machine Learning Foundations for CybersecurityЧтение
Demonstration: Introduction about Google Colab InterfaceВидео
Demonstration: Traditional vs AI-Driven Malware DetectionВидео
Demonstration: Using AI and Gen AI to Improve Password SecurityВидео
AI-Driven Threat Detection and Response in Modern CybersecurityЧтение
Test Your Knowledge: Leveraging AI and LLMs in CybersecurityЗадание

Applying and Securing AI and LLMs for Cyber Defense

Transformers: The AI BackboneВидеоFoundations of Transformers and Large Language ModelsЧтениеExploring Large Language Model ArchitecturesВидеоClassifying Key LLM Models (GPT, Gemini, LLaMA)ВидеоEvaluating LLM Capabilities and Limitations in CybersecurityВидеоSecure and Effective Use of LLMs in SOC OperationsЧтениеDemonstration: Using LLMs for Threat Detection and AnalysisВидеоDemonstration: Evaluating LLM Output for Security RisksВидеоTest Your Knowledge: Applying and Securing AI and LLMs for Cyber DefenseЗадание

Module Wrap-Up and Assessment

Module Summary: Artificial Intelligence and Large Language Models in CybersecurityЧтениеKnowledge Check: Artificial Intelligence and Large Language Models in CybersecurityЗаданиеStrengthening SIEM Monitoring and DoS Detection CapabilitiesDIALOGUE
02Prompt Engineering and AI System Security21 материалов

Foundations of Prompt Engineering for Secure AI

Introducing Prompt Engineering ConceptsВидеоCrafting Secure and Effective PromptsВидеоIdentifying Risks in Improper PromptingВидеоFoundations of Prompt Engineering for Secure and Effective LLM InteractionЧтениеExploring Advanced Prompting TechniquesВидеоDemonstration: Applying Prompt Engineering Techniques for Secure AIВидеоControlling AI Behavior Under AttackЧтениеTest Your Knowledge: Foundations of Prompt Engineering for Secure AIЗадание

Securing AI Systems and Defending Against Adversarial ML

Exploring AI System Architectures and ComponentsВидеоIdentifying Vulnerabilities Across AI PipelinesВидеоSecuring AI Systems: Architecture, Pipelines, and Attack SurfacesЧтениеUnderstanding Adversarial Machine Learning AttacksВидеоMethods of Crafting Adversarial AttacksВидеоAttacking and Hardening AI ModelsЧтение

Module Wrap-Up and Assessment

Module Summary: Prompt Engineering and AI System SecurityЧтениеStrengthening Defense Against Social Engineering and MalwareDIALOGUEKnowledge Check: Prompt Engineering and AI System SecurityЗадание
03Advanced Security, Ethics, and Governance for Generative AI37 материалов

Threats and Vulnerabilities in Generative AI Systems

Identifying Common Attack Vectors in Generative AI SystemsВидеоAnalyzing Prompt Injection AttackВидеоDemonstration: Containing Prompt Injection and Model AbuseВидеоExamining AI Jailbreak TechniquesВидеоDetecting Synthetic Content in Generative AIЧтениеExploring Model Theft and Extraction AttacksВидеоSecuring AI Data Against Poisoning RisksВидеоGenAI Risks in IoT and Physical SystemЧтениеTest Your Knowledge: Threats and Vulnerabilities in Generative AI SystemsЗадание

Leveraging Multimodal and Agentic AI for Security Automation

Introducing Multimodal AI for CybersecurityВидеоDemonstration: Applying Multimodal AI to Threat Detection Use CasesВидеоMultimodal and Agentic AI for SOC WorkflowsВидеоWorking of Agentic AI for SOC ЧтениеExploring Agentic AI for Cybersecurity OperationsВидеоDemonstration: Leveraging Agentic AI for Cybersecurity TriageВидео

AI Ethics, Governance, and Regulatory Compliance

Addressing Bias, Fairness, and Ethical Risks in AI SystemsВидеоWhen AI Trust Breaks: Ethical Risk ExplainedЧтениеEnsuring Transparency and Accountability in Generative AIВидеоAI Regulations and Risk Frameworks (GDPR, NIST, ISO)ВидеоProving Responsible AI: Audits and OversightЧтениеConducting AI Audits and Legal Risk AssessmentsВидео

Module Wrap-Up and Assessment

Module Summary: Advanced Security, Ethics, and Governance for Generative AIЧтениеSecuring Executive Approval for Post-Incident Resilience ImprovementsDIALOGUEKnowledge Check: Advanced Security, Ethics, and Governance for Generative AIЗадание

Course Wrap-Up and Assessment

Final Checkpoint: Integrating AI Security, Adversarial Defense, and Governance ControlsDIALOGUEPractice Project: Secure AI-Enabled SOC and Governance FrameworkЧтениеInterview: AI-Driven Security Operations and Secure AI Governance AssessmentDIALOGUEEnd Course Knowledge Check: Generative AI-Powered Security and SOC AutomationЗаданиеDesigning a Secure AI-Driven Security Operations FrameworkЗаданиеCourse SummaryВидео
Demonstration: Building Robust ML Models with Adversarial-Style TrainingВидео
Shielding AI Systems from Adversarial ThreatsВидео
Demonstration: Defending AI Systems Against Adversarial InputsВидео
Test Your Knowledge: Securing AI Systems and Defending Against Adversarial MLЗадание
Using Generative AI for Security Automation and IntelligenceВидео
GenAI for Security Automation and ResponseЧтение
Test Your Knowledge: Leveraging Multimodal and Agentic AI for Security AutomationЗадание
Test Your Knowledge: AI Ethics, Governance, and Regulatory ComplianceЗадание
Exploring AI Security Tool: Sola SecurityВидео
Ethical Screening Using Sola SecurityВидео
Describe Your Learning Journey Обсуждение