[center]Artifical Intelligence In Cybersecurity
Published 2/2026
Created by Rajesh Sinha
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 31 Lectures ( 8h 58m ) | Size: 7.8 GB [/center] How AI Powers Modern Threat Detection and Response What you'll learn
✓ Understand why AI is essential for detecting modern cyber threats beyond traditional rule-based security
✓ Explain how machine learning and deep learning are used in real-world cybersecurity operations
✓ See how AI fits across SOC architecture including email, EDR/XDR, SIEM, and SOAR
✓ Identify how NLP, CNNs, and RNNs are used for phishing, malware, and behavior-based threat detection Requirements
● Familiarity with basic IT fundamentals including networks, operating systems, and cloud environments
● No prior experience in Artificial Intelligence or data science is required
● No advanced programming or mathematics background is needed Description
Artificial Intelligence is rapidly transforming the cybersecurity landscape, reshaping how organizations detect, analyze, and respond to modern cyber threats. As attack volumes grow, threat actors become more sophisticated, and adversaries increasingly leverage automation and AI-driven techniques, traditional rule-based and manual security approaches are no longer sufficient on their own.
This course provides a comprehensive and practical introduction to the application of Artificial Intelligence in cybersecurity, with a strong focus on real-world security operations. Learners will gain a clear understanding of how machine learning and deep learning techniques are used to strengthen modern defense systems. The course explores key AI models, including Natural Language Processing for analyzing text-based threats such as phishing emails and security logs, Convolutional Neural Networks for malware and binary analysis, Recurrent Neural Networks for behavior and sequence-based attack detection, and Transformer-based models for context-aware threat intelligence and AI-powered SOC operations.
In addition to core concepts, the course demonstrates how AI is embedded across the security stack, from email security gateways and endpoint detection platforms to SIEM, SOAR, and AI-driven SOC assistants. Through real-world SOC scenarios and case studies, learners will see how AI enhances detection accuracy, reduces false positives, accelerates investigations, and supports faster, more informed decision-making.
Designed for cybersecurity professionals, IT practitioners, and technology leaders, this course equips learners with the knowledge needed to understand, evaluate, and apply AI-driven security capabilities, enabling them to build intelligent, resilient, and future-ready cybersecurity operations. Who this course is for
■ IT professionals and engineers who want practical insight into AI-driven security tools and platforms
■ Students and early-career professionals interested in cybersecurity and emerging AI technologies
■ Security architects and consultants evaluating AI-based security solutions
■ Technology leaders and managers seeking a strategic understanding of AI in cybersecurity
■ Cybersecurity professionals and SOC analysts looking to understand how AI enhances modern threat detection and response
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Artifical Intelligence In Cybersecurity
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