{"id":13576,"date":"2026-08-10T11:01:17","date_gmt":"2026-08-10T11:01:17","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-ai-for-cyber-security-threat-detection-soc-automation-2025-10\/"},"modified":"2026-08-10T11:01:17","modified_gmt":"2026-08-10T11:01:17","slug":"udemy-ai-for-cyber-security-threat-detection-soc-automation-2025-10","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-ai-for-cyber-security-threat-detection-soc-automation-2025-10\/","title":{"rendered":"Udemy \u2013 AI for Cyber Security : Threat Detection, SOC Automation 2025-10"},"content":{"rendered":"
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Descriptions<\/h2>\n

AI for Cyber Security : Threat Detection, SOC Automation, Artificial Intelligence is redefining the future of cybersecurity \u2014 and this course is your complete roadmap to mastering it. In AI for Cybersecurity: Threat Detection & SOC Automation, you\u2019ll learn how AI, Machine Learning (ML), and Deep Learning (DL) are transforming how organisations detect, prevent, and respond to cyber threats. This program blends real\u2011world labs, tools, and automation workflows to prepare you for the next generation of AI\u2011driven cybersecurity roles \u2014 from SOC analyst to security automation engineer. Modules cover foundations of AI in security, ML for anomaly and IDS enhancement, NLP for threat intelligence enrichment, AI\u2011powered SOAR and playbook automation, incident response optimisation, user behaviour analytics and graph\u2011based risk scoring, AI\u2011driven malware classification using sandboxing and EMBER, cloud and network security use cases, endpoint detection automation and federated learning, ethical limitations such as bias and false positives, and a capstone project to design an AI\u2011augmented SOC workflow. By the end of this course you\u2019ll be able to build, automate, and manage AI\u2011powered defence systems and apply them in cutting\u2011edge cybersecurity and AI operations roles.<\/p>\n

What you\u2019ll learn<\/h3>\n