To intelligently solve today’s various cybersecurity issues, popular AI techniques involving machine learning and deep learning methods, the concept of natural language processing, knowledge representation and reasoning, as well as the concept of knowledge or rule-based expert systems modeling can be used. In this course, you will learn about preparing the data for machine learning, common machine learning techniques and tools, and their applications to cybersecurity such as detecting anomalies, detecting known types of attacks like injections, clustering user activities, adversarial learning, etc. This course goes over the main disciplines of AI and explains how to apply these disciplines to solve pressing security problems, such as the challenges of data at scale and speed in threat response. Plus, you will learn how to best prepare your organization to apply AI-driven security.

Temps présentiel : 25 heures

Charge de travail étudiant : 50 heures

Méthode(s) d'évaluation : Examen écrit, Travaux pratiques