Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 5 Minute(s)
Language
English
Taught by
Learning Curve
Course Overview
Secure Generative AI Before It Breaks You — Master Risks, Defenses, and Real-World Protection
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 Course
What generative AI and LLMs are — and how they actually work
The full range of AI security risks: data leakage, model hallucinations, prompt injection, unauthorized access, deepfake abuse, and more
How to identify and prioritize AI risks using threat modeling frameworks like STRIDE and DREAD
The difference between public vs. private LLMs, and how to choose the right deployment for your security and compliance needs
How to create a secure AI usage policy for your team or organization
Step-by-step strategies to prevent AI-powered phishing, malware generation, and supply chain attacks
Best practices for sandboxing, API protection, and real-time AI monitoring
Why This Course Stands Out
This 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 deployed
Communicate AI threats and solutions with confidence to your team or executives
Implement technical and governance controls that actually work
Lead the secure adoption of AI tools in your business or organization
Who This Course Is For
This course is for anyone looking to build or secure generative AI systems, including:
Cybersecurity analysts, architects, and engineers
CISOs, CTOs, and IT leaders responsible for AI adoption
Risk and compliance professionals working to align AI with regulatory standards
Developers and AI/ML engineers deploying language models
Product managers, legal teams, and business stakeholders using AI tools
Anyone curious about AI security, even with minimal technical background
No Technical Experience Required
You 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 Policy
You’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 vulnerabilities
Securely integrate tools like ChatGPT and other LLMs
Prevent insider misuse and external attacks
Translate technical threats into strategic action
Confidently lead or contribute to responsible AI adoption
Course Content
- 3 section(s)
- 21 lecture(s)
- Section 1 Introduction
- Section 2 Generative AI Risks and Threats
- Section 3 Making Generative AI Safe
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
