This is an interactive course, with the goal of teaching security professionals how to implement data science techniques in order to obtain valuable insights. This course will encompass various topics including: feature engineering, exploratory data analysis, data visualization, machine learning and probabilistic graphical models. I believe the combination of data science and security allows the security community to move our assumptions, opinions and beliefs into knowledge. This two day course teaches attendees the data science concepts, techniques and processes for analyzing various security datasets.

No previous data science experience is necessary as this course is designed for those who are new to data science. Background understanding programming is very helpful, specifically Python.

Instructor BIO:

Shane McFly is a senior cybersecurity researcher for a federally funded research and development center. He is part of a research group there that focuses on the cyber physical systems security challenges specific to the next generation of the nation’s critical infrastructure. He earned his Masters and Bachelors degrees in Computer Science from the University of Illinois and is currently pursuing his PhD in computer science (and teaching) with a focus on cyber physical systems security at the Colorado School of Mines. His research interests include cyber defense exercises and competitions as well as workforce development.