{"id":13162,"date":"2026-08-10T10:55:28","date_gmt":"2026-08-10T10:55:28","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/oreilly-machine-learning-and-ai-in-cybersecurity-2025-3\/"},"modified":"2026-08-10T10:55:28","modified_gmt":"2026-08-10T10:55:28","slug":"oreilly-machine-learning-and-ai-in-cybersecurity-2025-3","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/oreilly-machine-learning-and-ai-in-cybersecurity-2025-3\/","title":{"rendered":"Oreilly \u2013 Machine Learning and AI in Cybersecurity 2025-3"},"content":{"rendered":"
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Description<\/span><\/h2>\n

Machine Learning and AI in Cybersecurity. This course explores how machine learning and artificial intelligence technologies can be used to identify and combat cyber threats. This course provides a practical approach to integrating AI-based solutions into security frameworks. Topics begin with the basics of machine learning and Python programming, and then move on to building, analyzing, and optimizing machine learning models for cybersecurity applications. Topics covered include neural networks, clustering techniques, and self-organizing maps, with practical examples such as intrusion detection systems, malware countermeasures, log analysis, and vulnerability management. This course is taught by Dr. Chuck Eastum, a leading cybersecurity expert and holder of 26 patents, and is designed for cybersecurity professionals, software developers, and IT professionals. By completing this course, participants will gain the knowledge and tools necessary to effectively use artificial intelligence to increase the security of digital environments. Prerequisites for this course include familiarity with basic cybersecurity concepts and a basic understanding of the Python language, the introductory concepts of which will be reviewed throughout the course.<\/span><\/p>\n

What you will learn<\/span><\/h3>\n