Description
Introduction
Organizations now confront a significant cybersecurity threat, ranging from rogue URLs to credential reuse and having reliable security solutions may make all the difference. You’ll learn how to leverage libraries like TensorFlow and scikit-learn to build cutting-edge artificial intelligence (AI) approaches and solve problems that cybersecurity researchers encounter.
By learning about different machine learning (ML) approaches and how to build up a safe lab environment. This webinar will teach you how to build malware classifiers and features, which you will then train and test on actual samples. You’ll master the fundamentals of self-learning, self-reliant systems for cybersecurity tasks including detecting harmful URLs, spam email detection, intrusion detection, network protection, and user and process activity tracking.
Highlights of Webinar
- Understand the key concepts of predicting cybersecurity threats with artificial intelligence.
- Understand the fundamentals on how to develop intelligent systems that can detect unusual and suspicious pasterns.
- Understand the testing mechanism of your AI Cybersecurity code and tools.
Who can attend?
Cyber security professionals, enthusiasts, Incident responders, threat hunters, CISOs and cyber security students.
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