Free Download Udemy - Generative AI Security Masterclass Risks, Threats & Defense
Published: 4/2025
Created by: Learning Curve
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Expert | Genre: eLearning | Language: English | Duration: 21 Lectures ( 2h 5m ) | Size: 909 MB
Secure Generative AI Before It Breaks You - Master Risks, Defenses, and Real-World Protection
What you'll learn
The fundamentals of generative AI and Large Language Models (LLMs)
The top security threats: data leakage, prompt injection, deepfakes, hallucinations
How to perform AI threat modeling using STRIDE and DREAD
Key differences between public and private LLMs - and when to use each
How to create and implement an AI security policy
Hands-on strategies to defend against AI misuse and insider risk
Practical examples of real-world incidents and how to prevent them
Requirements
A basic understanding of AI or cybersecurity concepts
No coding experience required
Curiosity and commitment to building secure AI systems
Description
Welcome to the Generative AI Security Masterclass - your practical guide to navigating the risks, threats, and defenses in the age of AI.Generative AI tools like ChatGPT, Bard, Claude, and Midjourney are changing the way we work, code, communicate, and innovate. But with this incredible power comes a new generation of threats - ones that traditional security frameworks weren't designed to handle.This course is designed to help you understand and manage the unique security risks posed by generative AI and Large Language Models (LLMs) - whether you're a cybersecurity expert, tech leader, risk manager, or just someone working with AI in your daily operations.What You'll Learn in This CourseWhat generative AI and LLMs are - and how they actually workThe full range of AI security risks: data leakage, model hallucinations, prompt injection, unauthorized access, deepfake abuse, and moreHow to identify and prioritize AI risks using threat modeling frameworks like STRIDE and DREADThe difference between public vs. private LLMs, and how to choose the right deployment for your security and compliance needsHow to create a secure AI usage policy for your team or organizationStep-by-step strategies to prevent AI-powered phishing, malware generation, and supply chain attacksBest practices for sandboxing, API protection, and real-time AI monitoringWhy This Course Stands OutThis is not just another theoretical AI class.You'll explore real-world security incidents, watch hands-on demos of prompt injection attacks, and build your own custom AI security policy you can actually use.By the end of this course, you'll be ready to:Assess the risks of any AI system before it's deployedCommunicate AI threats and solutions with confidence to your team or executivesImplement technical and governance controls that actually workLead the secure adoption of AI tools in your business or organizationWho this course is for This course is for anyone looking to build or secure generative AI systems, including:Cybersecurity analysts, architects, and engineersCISOs, CTOs, and IT leaders responsible for AI adoptionRisk and compliance professionals working to align AI with regulatory standardsDevelopers and AI/ML engineers deploying language modelsProduct managers, legal teams, and business stakeholders using AI toolsAnyone curious about AI security, even with minimal technical backgroundNo Technical Experience RequiredYou don't need to be a programmer or a machine learning expert. If you understand basic cybersecurity principles and have a passion for learning about emerging threats, this course is for you.Course Project: Your Own AI Security PolicyYou'll apply what you've learned by building a generative AI security policy from scratch - tailored for real-world use inside a company, government, or startup. By the End of This Course, You'll Be Able To:Recognize and mitigate generative AI vulnerabilitiesSecurely integrate tools like ChatGPT and other LLMsPrevent insider misuse and external attacksTranslate technical threats into strategic actionConfidently lead or contribute to responsible AI adoption
Who this course is for
Cybersecurity professionals: Analysts, engineers, architects, red/blue teams
CISOs and IT leaders: Decision-makers responsible for secure AI adoption
Compliance and risk officers: Aligning AI with legal, regulatory, and internal frameworks
AI and IT specialists: Developers, ML engineers, and sysadmins working with LLMs
Legal advisors, product managers, and innovators looking to understand secure AI use
Anyone with a basic understanding of AI and cybersecurity who wants to take their knowledge deeper
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