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Artificial Intelligence Risks In Cybersecurity
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charlie
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3 898 posts 3 898 threads Dołączył: Nov 2025
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[center][Obrazek: c76c67688709dd53c89666a67f3320b3.jpg]
Artificial Intelligence Risks In Cybersecurity
Published 12/2025
Created by Syed Muhammad Hatim Javaid
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 32 Lectures ( 4h 1m ) | Size: 3.33 GB[/center]

Master AI Governance, Secure LLMs, and Mitigate Generative AI Risks using NIST Frameworks. (Focuses on frameworks and LL
What you'll learn
Students will learn the core fundamentals of AI governance and risk management through industry-standard frameworks like NIST.
The course provides deep insights into securing Large Language Models (LLMs) against specific threats like prompt injections, hallucinations, and SSRF.
Learners will discover how to identify and mitigate ethical risks, including model bias and data privacy concerns in generative systems.
Students will master defensive strategies to protect against data leakage, data poisoning, and evolving cyber-attacks from AI-powered threat actors.
By the end, students will be equipped with practical tools and checklists to implement robust AI security and compliance within any organization.
Requirements
A basic understanding of how computer systems and the internet function is required to navigate the course material.
No advanced programming skills or prior experience in artificial intelligence development are necessary to begin.
A foundational interest in cybersecurity and emerging technologies will help you better understand the threat mitigation strategies.
Familiarity with general IT or business terminology is helpful for the sections on governance and risk management frameworks.
An eagerness to explore the ethical, legal, and security challenges posed by modern AI systems is the most important prerequisite.
Description
Are you ready to stay ahead of the next wave of digital threats? As Artificial Intelligence transforms the global tech landscape, it brings a new set of sophisticated vulnerabilities. This theory-based course is a comprehensive guide designed for those who want to understand the strategic, ethical, and technical risks inherent in AI systems without needing to write a single line of code.Master the Strategy Behind AI DefenseIn this course, we move beyond the hype to explore the actual mechanics of AI vulnerabilities. From the foundational principles of AI Governance to the intricate security challenges of Large Language Models (LLMs), you will learn how to identify, assess, and mitigate risks using industry-standard frameworks like NIST.What You Will ExploreThe Foundation of AI Governance: Learn how to build and implement a robust governance framework for any organization.Securing Generative AI: Understand the specific risks of LLMs, including Prompt Injections, Hallucinations, and Data Leakage.Advanced Cyber Threats: Explore how modern threat actors use AI for Data Poisoning, SSRF, and sophisticated DDoS attacks.Ethics & Legality: Navigate the complex world of Model Bias, AI copyright issues, and the legal implications of automated decision-making.Practical Implementation: Gain access to an exclusive AI Governance Checklist to audit and secure AI systems effectively.Why Choose This Course?This is a strictly theory-based course, making it perfect for professionals who need to understand the "Why" and "How" of AI security without getting bogged down in programming. It is ideal for decision-makers, auditors, and security enthusiasts who want a high-level, strategic understanding of the AI threat landscape.Who Is This For?Cybersecurity professionals looking to pivot into AI security.IT Managers and Compliance Officers overseeing AI integration.Legal and Ethical consultants focused on emerging tech.Students wanting to master the theory of AI risk management.Equip yourself with the knowledge to secure the future. Enroll today and master the critical intersection of Artificial Intelligence and Cybersecurity!
Who this course is for
Cybersecurity professionals and ethical hackers who want to specialize in securing AI infrastructure and Large Language Models.
IT managers and organizational leaders responsible for implementing AI governance and risk management frameworks.
Compliance officers and legal professionals interested in the ethical, legal, and copyright challenges of generative AI.
Security auditors who need practical methodologies and checklists for evaluating the vulnerabilities of AI systems.
Students and tech enthusiasts looking to stay ahead of the curve by understanding defense strategies against modern AI-driven cyber threats.
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