online & regional CourseApplied Data Science and Machine Learning

Quickly manipulate and analyze network and security data and ultimately uncover valuable insights from your discovery.

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Course Details
Course Level
full
Course Length
32 Hrs
Minimum Class Size
5 Students
Course Platform
online & regional
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Course Overview

This interactive course will teach cybersecurity 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.

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Once You’ve Completed This Course You Have The Skills To:

Read data in a variety of common formats then write scripts to analyze and visualize that data.


Course Objectives

Rapidly explore, visualize and analyze security data using open source tools
Construct, train, evaluate and deploy supervised machine learning models to solve difficult security related problems
Construct unsupervised models for anomaly detection and other exploratory analysis

The Fine Print

Course Size Requirements

GTK has a 5 student minimum for courses and no maximum head count. Head count must be locked in at the time of contract.

US Travel / Incidental Cost

  • U.S. Travel/Incidental cost is $500 per day.
  • Virtual courses do not incur travel/incidental costs.
  • No Travel/Incidental costs are charged for local courses (MD/DC/VA corridor).

Course Format

  • Instructors typically teach 50% of the day, and run training simulations for the other 50%.
  • GTK typically uses Google Meets for virtual courses, but can use any service with advanced notice.

[The GTK Cyber course] was well organized and flowed nicely, all of the topics were relevant.

Former Student

I found it informative and interesting.

Former Student

The Jupyter notebooks and answers were a big help.

Former Student

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