{"id":9982,"date":"2026-08-10T10:13:38","date_gmt":"2026-08-10T10:13:38","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-hands-on-ai-llm-red-teaming-2025-9\/"},"modified":"2026-08-10T10:13:38","modified_gmt":"2026-08-10T10:13:38","slug":"udemy-hands-on-ai-llm-red-teaming-2025-9","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-hands-on-ai-llm-red-teaming-2025-9\/","title":{"rendered":"Udemy \u2013 Hands On AI (LLM) Red Teaming 2025-9"},"content":{"rendered":"
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Description<\/span><\/h2>\n

Hands On AI (LLM) Red Teaming Course. This course is a hands-on training program in the field of AI security that focuses specifically on the concept of Red Teaming for Large Language Models (LLM). The main goal of this course is to empower offensive cybersecurity researchers, AI professionals, and cybersecurity team managers with the skills needed to identify and exploit vulnerabilities in AI systems for ethical purposes, defend these systems against attacks, and implement AI governance and safety measures in organizations. During this course, participants will gain a deep understanding of the risks and vulnerabilities associated with productive AI. They will also explore regulatory frameworks such as the EU AI Law and emerging AI safety standards. A significant portion of the course is dedicated to gaining practical skills in testing and securing LLM systems.<\/span><\/p>\n

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The course structure includes a variety of topics. In the introduction section, participants will be introduced to the concept of red teaming in AI, the architecture of large language models, the risk classification associated with LLM, and an overview of red team strategies and tools. Then, techniques for breaking LLM, practical exercises for vulnerability testing, and the concept of Prompt Injection attacks along with its difference from breaking LLM will be examined. Techniques for performing and preventing command injection attacks and practical exercises with RAG (Recovery-Based Generation) and Agent architectures will be presented. A key part of the course is a review of the OWASP Top 10 Risks for LLM, which includes understanding common risks, practical demonstrations to solidify the concepts, and guided red team exercises to test and mitigate these risks. Finally, implementation tools and resources will be introduced, including Jupyter notebooks, templates and tools required for red teams, as well as a classification of security tools for implementing protections and monitoring solutions.<\/span><\/p>\n

What you will learn<\/span><\/strong><\/h3>\n