Udemy - LLM and Generative AI Security - Protect AI Applications
About Udemy - LLM and Generative AI Security - Protect AI Applications
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LLM & Generative AI Security: Protect AI Applications https://WebToolTip.com Published 8/2026 Created by Data Science Academy, School of AI MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All Levels | Genre: eLearning | Language: English | Duration: 15 Lectures ( 4h 26m ) | Size: 1.7 GB Secure ChatGPT, Claude, AI Agents & RAG Applications with Prompt Injection Defense, Guardrails, OWASP LLM Top 10 What you'll learn ⚡ Identify and understand major LLM and Generative AI se
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LLM & Generative AI Security: Protect AI Applications
https://WebToolTip.com
Published 8/2026
Created by Data Science Academy, School of AI
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 15 Lectures ( 4h 26m ) | Size: 1.7 GB
Secure ChatGPT, Claude, AI Agents & RAG Applications with Prompt Injection Defense, Guardrails, OWASP LLM Top 10
What you'll learn
⚡ Identify and understand major LLM and Generative AI security threats, including prompt injection, jailbreaking, data leakage, insecure output handling
⚡ Apply the OWASP guidance for LLM and Generative AI applications to assess vulnerabilities and strengthen AI application security.
⚡ Design and secure Retrieval-Augmented Generation (RAG) systems against document poisoning, retrieval attacks, unauthorized access, and vector database risks.
⚡ Protect AI agents and tool-calling systems using least privilege, permission controls, human approval workflows, and secure MCP practices.
⚡ Secure AI APIs and integrations using authentication, authorization, secrets management, rate limiting, and secure API design principles.
⚡ Implement AI guardrails using input filtering, output validation, content moderation, policy enforcement, and human-in-the-loop controls.
⚡ Perform AI red teaming using adversarial prompts, jailbreak testing, prompt fuzzing, and structured security-testing methodologies.
⚡ Build practical AI threat models by identifying assets, data flows, trust boundaries, threat actors, and attack paths.
Requirements
❗ No prior AI security experience is required. The course starts with the fundamentals and progressively introduces more advanced security concepts.
❗ A basic understanding of cybersecurity, networking, or application security is helpful but not required.
❗ Basic familiarity with Artificial Intelligence, ChatGPT, or other Generative AI tools will be useful.
❗ Basic Python or programming knowledge is helpful for hands-on exercises, but advanced coding skills are not required.
❗ A computer running Windows, macOS, or Linux with a modern web browser and internet connection.