Explore the crucial relationship between artificial intelligence and cybersecurity including vulnerabilities and security risks associated with LLMs and other machine learning models.
Artificial Intelligence and Cybersecurity
1h 4m 21s
English
Paid
AI is changing the cybersecurity landscape, creating unparalleled tools for defending digital assets while also creating new attack vectors and vulnerabilities. It's a bit of a double-edged sword, but one that every Cybersecurity professional will need to learn to wield.
About the Author: Zero To Mastery
Zero To Mastery (ZTM) is a Toronto-based online coding academy founded by Andrei Neagoie, originally a senior developer at large Canadian tech firms before turning to teaching full-time. The academy's signature is the cohort-based bootcamp track combined with a deep self-paced course library, all aimed at career-changers and self-taught developers preparing to land software-engineering roles at top companies.
The instructor roster has grown well beyond Andrei to include other senior practitioners: Daniel Bourke (machine learning), Aleksa Tešić (DevOps), Jacinto Wong, and others. Courses cover the full software-engineering career path: web development with React and Next.js, Python, machine learning and deep learning, DevOps and cloud, system design, mobile, and the algorithm / data-structure interview prep that gates engineering jobs.
The CourseFlix listing under this source carries over 120 ZTM courses spanning that full range. Material is paid; ZTM itself runs on a monthly / annual membership model. The teaching style favours long-form, project-based courses where students build complete portfolio-quality applications rather than disconnected feature tutorials.
Watch Online 7 lessons
0:00
/ #1: Introduction to AI in Cybersecurity
All Course Lessons (7)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | Introduction to AI in Cybersecurity Demo | 06:52 | |
| 2 | Bypassing ChatGPT Ethical Filters | 18:58 | |
| 3 | Jailbreak Chat | 10:24 | |
| 4 | AI & Machine Learning Security Risks | 04:33 | |
| 5 | Next Gen Social Engineering Attacks | 08:56 | |
| 6 | Primary Security Risk When Using AI | 07:33 | |
| 7 | Benefits of AI in Cybersecurity | 07:05 |
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Frequently asked questions
What prior knowledge is required before taking this course?
The course is designed for individuals with a basic understanding of both artificial intelligence and cybersecurity. Familiarity with machine learning concepts and general cybersecurity principles will help in grasping the course content more effectively. However, the course begins with an introductory lesson, which provides foundational knowledge about AI in cybersecurity, making it accessible to those with less experience in these areas.
What practical skills will I gain from this course?
Participants will learn about the vulnerabilities and security risks associated with large language models (LLMs) and machine learning models. The course includes lessons on bypassing ethical filters in AI tools like ChatGPT and understanding how AI can be used in next-generation social engineering attacks. These skills are crucial for identifying and mitigating AI-related security threats.
Who is the intended audience for this course?
This course is intended for cybersecurity professionals, AI enthusiasts, and IT specialists interested in understanding the intersection of artificial intelligence and cybersecurity. It's also beneficial for individuals looking to enhance their skills in identifying and managing AI-driven security risks in various environments.
How does the depth of this course compare to similar courses?
This course provides a focused exploration of AI-related cybersecurity challenges, specifically targeting vulnerabilities in machine learning models and the ethical implications of AI use. Compared to broader AI courses, it offers specialized insights into AI's role in cybersecurity, making it suitable for learners interested in deepening their expertise in this niche area.
What specific tools or platforms will I learn about?
The course addresses specific tools and platforms such as ChatGPT, providing insights into bypassing its ethical filters and understanding the associated security risks. This practical knowledge is essential for professionals aiming to secure AI deployments and protect against AI-driven social engineering attacks.
What topics are not covered in this course?
The course does not delve into general AI development techniques or non-security-related AI applications. Its focus is strictly on the intersection of AI and cybersecurity, including security risks, vulnerabilities, and the potential benefits AI brings to cybersecurity measures.
How much time should I expect to commit to this course?
The course is structured into seven lessons, allowing learners to progress at their own pace. Although the exact runtime is not specified, students should allocate adequate time to fully engage with each lesson and the associated material to gain a comprehensive understanding of AI and cybersecurity interdependencies.