October 12

GTK Public Class – Fall 2021

Applied Data Science and Machine Learning for Cybersecurity

Applied Data Science and Machine Learning for Cybersecurity

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Why Choose Our Course?

Huge Demand
Cybersecurity Community
Our philosophy ensures that our students gain an enhanced grasp on the principles behind the software. This method makes professionals more proficient and effective in their positions. It gives them the power to apply those processes and methodologies to any software.

Difficulty

Intermediate / ADVANCED

Learning Period

4 Weeks

Knowledge Required

Python

Course Language

English

Applied Data Science for Cybersecurity

Learn how to quickly manipulate
and analyze network and security data

Expand your thinking
Solve Technical Issues
Practice Projects
Requires Basic Knowledge of Python
Experienced Instructors
Online Community

All You Need To Know

About This Course

deadline

This course will be offered over four (4) weeks. Each week will have a total of eight hours of coursework spread out over two disparate days. The course will be taught from 12:00 p.m. until 4:00 p.m. each day. (1200-1600) The course dates are:

  • October 12, 14, 19, 21, 26 & 28
  • November 2 & 4
report

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.

win

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.
question

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
logical-thinking

Intermediate/Advanced

checklists

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.

info

For more information about the course, please check out our Applied Data Science for Cybersecurity page or download the course flyer here.

 

CEO, DATA SCIENTIST

charles givre, CISSP

Charles Givre is a solutions-focused Senior Technical Executive and Data Scientist with 20+ years of success across the technology, data science, fintech, education, and cybersecurity industries.

Upgrade Your Data Science Knowledge Now!

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Student Feedback

Good introduction into the topic of machine learning, plenty of hands-on experience with jupyter/python/pandas/etc. This fit exactly with what we are doing in our daily work so was directly applicable.
Threat Hunter
ING.com
The first iteration of the course packed all relevant concepts and exercises in a fast-paced manner. That was personally valuable as a refresher due to my academic background with some touchpoints on machine learning.
Senior Cybersecurity Analyst
Booking.com

Grab This Opportunity Now

This course will be offered over four (4) weeks. Each week will have a total of eight hours of coursework spread out over two disparate days. The course will be taught from 12:00 p.m. until 4:00 p.m. each day. (1200-1600) The course dates are:

  • October 12, 14, 19, 21, 26 & 28
  • November 2 & 4

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.

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.

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

Intermediate/Advanced

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.

For more information about the course, please check out our Applied Data Science for Cybersecurity page or download the course flyer here.

 

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Event Details
Start Date
October 12, 2021
End Date
November 4, 2021
Times
12:00 PM - 4:00 PM
Location
Virtual Event
Admission
Cost: $4,000
This course is designed for cybersecurity professionals that are new to data science or machine learning but want to use these techniques in real world applications.
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