Free Download Generative AI Privacy & Security OWASP & NIST for Devs
Published 8/2026
Created by ACHRAF ER-RAYA
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 6 Lectures ( 1h 15m ) | Size: 562.4 MB
Master Generative AI data privacy with OWASP, NIST AI RMF, secure RAG, LLMOps, threat modeling and privacy testing.
What you'll learn
Neutralize the OWASP Top 10 vulnerabilities specific to Large Language Models before deployment. Build Python-based middleware to automatically redact PII before it reaches external AI APIs. Defend AI agentic workflows and chains against direct and indirect prompt injection attacks. Implement Zero-Trust architecture and strict Role-Based Access Controls in RAG systems.Requirements
Basic understanding of Python or JavaScript and familiarity with REST APIs. No prior cybersecurity expertise or advanced machine learning knowledge is required-we build the security layers from scratch.Description
"This course contains the use of artificial intelligence."
Build GenAI applications that can demonstrate how sensitive information is controlled-not merely promise that it is.
Generative AI introduces new data flows across prompts, models, RAG systems, vector stores, tools, APIs, caches, and telemetry. This developer-focused course converts privacy and AI-risk guidance into technical architecture, implementation controls, tests, and review evidence.
Who this course is for
Backend Developers, Full-Stack Engineers, and AI Integration Specialists tasked with integrating LLMs into enterprise applications who need to guarantee data privacy and pass strict security compliance audits.Homepage
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