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.

About the instructor: Imani Palmer I am a highly motivated research scientist that focuses in the area of security. I earned a PhD in Computer Science from the University of Illinois. I current work in the space of data science and security on multiple projects from cyber risk, education and low-level kernel analysis.