Machine Learning in Cybersecurity

Duration

40 hours (online | offline)

Language

Ukrainian / Russian

Audience
Students / PhD students, engineers, teachers, researchers and professionals in cybersecurity, information security, telecommunications, information technologies, as well as CTO, CIO and CRO.
Description

This course focuses on the current advances and future directions in the research of machine learning technologies and their practical application. The main types of machine learning tasks in cybersecurity as well as the main types of machine learning models, such as linear, metric, probabilistic and other models, will be analyzed. The usage of decision trees, neural networks, and ensembles of decision rules in incident detection and threat categorization tasks will be covered. In addition, the course explains the process of machine learning experiments and the interpretation of their results in cybersecurity systems.

Trainer

Viktoriia Sydorenko
PhD, Associate Professor in Information Security,
National Aviation University, Kyiv, Ukraine

EnglishUkraine
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