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via Udemy |
Go to Course: https://www.udemy.com/course/genai-cybersecurity-owasp-mitre-atlas-api-attcks-in-hindi/
Certainly! Here's a detailed review and recommendation for the "GenAI Cybersecurity ka Beginner-Friendly Course, ab Hindi mein!" available on Coursera: --- **Course Title:** GenAI Cybersecurity ka Beginner-Friendly Course, ab Hindi mein! **Overview:** This beginner-friendly course on Coursera offers an in-depth introduction to the intersection of Generative AI (GenAI) and cybersecurity, specifically focusing on Large Language Models (LLMs). Designed for enthusiasts, AI developers, and IT students, the course provides a comprehensive blend of theoretical foundations and practical applications, all explained in Hindi to make complex topics accessible. **What You Will Learn:** - The fundamental architecture of LLMs, including Transformer models - The evolution of neural networks from RNNs to Transformers - Core concepts such as Positional Encoding, Self-Attention, and Multi-Head Attention - Layers within LLM systems: Application, AI Model, and Integration layers - Various attack surfaces from consumer-side threats (prompt injection, data leakage) to provider-side risks (model theft, insecure endpoints) - Key cybersecurity frameworks like OWASP Top 10 for LLMs and MITRE ATLAS threat mapping - Practical demonstrations of vulnerabilities and their mitigations, including API misconfiguration and insecure endpoints - Real-world case studies highlighting threats like model theft, data leaks, output poisoning, and unexpected AI behavior **Course Structure:** The course begins with a solid theoretical foundation, explaining how LLMs are built using Transformer architectures, and then progresses to practical attack scenarios and case studies. Hands-on labs like API misconfiguration mitigation with NGINX and exploration of API vulnerabilities provide valuable practical experience. By analyzing real-world incidents involving OpenAI, Microsoft, and other organizations, learners gain insight into potential security challenges. **Who Should Enroll:** - Beginners interested in AI and cybersecurity - AI developers aiming to understand security vulnerabilities - IT students looking to expand their knowledge in emerging AI security issues - Professionals seeking a Hindi-language resource to grasp complex GenAI security concepts **Why Recommend This Course:** - **Language Accessibility:** Delivered entirely in Hindi, making complex cybersecurity concepts more understandable for Hindi-speaking learners. - **Comprehensive Curriculum:** Covers both theoretical underpinnings and practical security measures, ensuring well-rounded knowledge. - **Practical Labs & Case Studies:** Offers hands-on experience with real-world scenarios, crucial for applied learning. - **Focus on Current Threats & Frameworks:** Incorporates industry-standard frameworks like OWASP and MITRE, aligning with current cybersecurity practices. - **Career Guidance:** Provides tips for building a career at the intersection of AI and cybersecurity, including skill development and online presence. **Final Verdict:** This course is highly recommended for anyone looking to build a solid foundation in GenAI security from scratch, especially Hindi-speaking learners who find English materials challenging. Its mix of theory, practical demos, and real-world cases makes it a valuable resource for aspiring cybersecurity professionals and AI enthusiasts aiming to understand how to secure advanced AI systems. --- **Enroll today to start your journey into securing the future of Generative AI systems!**
GenAI Cybersecurity ka Beginner-Friendly Course, ab Hindi mein!Agar aap ek cybersecurity enthusiast ho, AI developer ho ya IT student, yeh course aapko theoretical aur practical dono knowledge dega - specifically Large Language Models (LLMs) ko secure karne ke liye, jo GenAI ecosystem ka core part hain.Course ka Structure:Pehle hum ek strong theory base banate hain: • LLMs kaise bante hain using Transformer architecture • Neural Networks ka evolution: RNNs se leke Transformers tak • Important concepts jaise: • Positional Encoding • Self-Attention • Multi-Head AttentionPhir aate hain LLM system ke layers: • Application Layer • AI Model Layer • Integration LayerAttack Surfaces samjhte hain do perspectives se: • Consumer-side attacks jaise prompt injection, data leakage • Provider-side risks jaise model theft, insecure endpointsOWASP Top 10 Risks for LLMs aur MITRE ATLAS threat mapping bhi cover karenge.Practical Demos bhi milenge: • OLLAMA API misconfiguration demo + uska mitigation using NGINX • PortSwigger Lab on LLMs with excessive API agencyReal-World Case Studies: • OpenAI vs. DeepSeek - Model theft aur distillation issues • Microsoft Tay - Output poisoning and moderation ka lack • Wiz Cloud Logs Leak - Prompt aur data ka exposure • Chevrolet AI Chatbot - AI agents behaving unexpectedly • OLLAMA API Exposure - No auth pe open endpointsCareer Tips & Roadmap: • AI/ML fundamentals build karna • GenAI + Cybersecurity ka intersection samajhna • Hands-on skills kaise develop karein • Apna professional presence online grow karnaTopics Covered: • GenAI Cybersecurity • Large Language Models (LLMs) • Transformer Architecture • Self-Attention, Multi-Head Attention • LLM System Architecture • OWASP LLM Top 10 • MITRE ATLAS Threat Mapping • Practical Labs • LLM Security Real-World Examples