Generative AI for Security Fundamentals

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Generative AI for Security Fundamentals

Coursera · Intermediate ·🧠 Large Language Models ·3mo ago

Key Takeaways

Securing AI-driven systems using Generative AI and Large Language Models

Original Description

This program equips cybersecurity professionals, IT teams, and business leaders with foundational knowledge and practical skills to secure AI-driven systems using Generative AI and Large Language Models (LLMs). You’ll start by understanding AI’s role in cybersecurity, exploring traditional security methods, LLM architectures, and how GenAI applications are transforming threat detection and defense mechanisms. Next, you’ll dive into Generative AI security fundamentals, learning prompt engineering techniques, risks of manipulation, and how to securely design interactions with AI models. You’ll also gain hands-on experience applying LLMs to threat analysis, identity management, and security automation. By the end of this program, you will be able to: - Explain the foundational concepts of AI and its implications for cybersecurity. - Differentiate between traditional AI, LLMs, and Generative AI applications in security contexts. - Apply secure prompt engineering methods and mitigate risks associated with AI interactions. - Use LLMs to enhance threat detection, identity management, and automation in security workflows. - Identify vulnerabilities in AI architectures and implement best practices to secure models - Understand adversarial machine learning techniques and deploy defenses to protect AI systems. - Evaluate AI-driven security processes for ethical, transparent, and resilient operations. This course is designed for cybersecurity engineers, AI security specialists, LLM engineers, ML engineers, and cloud/edge security architects looking to build expertise in AI security. Join us to develop the skills needed to protect modern cybersecurity environments with AI-powered solutions and best practices.
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