November 08

Black Hat Europe 2021

Applied Data Science and Machine Learning for Cybersecurity

This interactive course will teach security professionals how to use data science techniques to quickly manipulate and analyze network and security data and ultimately uncover valuable insights from this data. The course will cover the entire data science process from data preparation, feature engineering and selection, exploratory data analysis, data visualization, machine learning, model evaluation and optimization and finally, implementing at scale—all with a focus on security-related problems.


KEY TAKEAWAYS

By the end of the course, students will be able to:

  • Use the python data science ecosystem to rapidly prepare, explore and visualize cybersecurity data
  • Build and evaluate common machine learning models and apply these techniques to cybersecurity use cases
  • Develop unsupervised models to uncover anomalies and other patterns in their cybersecurity data.

WHO SHOULD TAKE THIS COURSE

Anyone who wishes to incorporate automated data analysis, machine learning and data science into their cybersecurity work. Particularly those working in the following job roles:

  • Security Analyst
  • SOC Analysts
  • SOC Engineers
  • CND Analysts
  • Security Monitoring
  • System Administrators
  • Cyber Threat Investigators
  • Individuals working on a network hunt team

AUDIENCE SKILL LEVEL

Intermediate/Advanced

STUDENT REQUIREMENTS

This is a hands-on course. To get the most out of the class and labs, students should be comfortable coding in Python as well as understand common security and network concepts.

Event Details
Start Date
November 8, 2021
End Date
November 11, 2021
Times
9:00 AM - 5:00 PM
Location
Virtual Event
Add to Calendar