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Applied Data Science for Cyber Security

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. You will learn how to read data in common formats and write scripts to analyze and visualize that data. Topics range from data preparation and machine learning to model evaluation, optimization and implementation—at scale.

Provider Information

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Contact Information

1152 Tyler Ave
Annapolis, MD 21403

Course Overview

Overall Proficiency Level
2 - Intermediate
Course Prerequisites

Students should have: - Fundamentals Object-Oriented Programming
- All Skill-Levels (Challenges for Beginner to Pro Programmers)
- All Backgrounds (From IT, Cyber SME to Manager)

Training Purpose
Functional Development
Skill Development
Specific Audience
All
Delivery Method
Online, Instructor-Led
Classroom
Course Location

7000 Columbia Gateway Drive
Suite 150
Columbia, MD 21046

  • Online, Instructor-Led
  • Classroom

Learning Objectives

Write scripts to efficiently read and manipulate CSV, XML, and JSON files
Quickly and efficiently parse executables, log files, pcap and extract artifacts from them
Make API calls to merge datasets
Use the Pandas library to quickly manipulate tabular data
Effectively visualize data using Python
Pre-process raw security data for machine learning and feature engineering
Build, apply and evaluate machine learning algorithms to identify potential threats
Automate the process of tuning and optimizing machine learning models
Hunt anomalous indicators of compromise and reducing false positives
Use supervised learning algorithms such as Random Forests, Naive Bayes, K-Nearest Neighbors (K-NN) and Support Vector Machines (SVM) to classify malicious URLs and identify SQL Injection
Apply unsupervised learning algorithms such as K-Means Clustering to detect anomalous behavior
Finally, you will be introduced to cutting edge Big Data tools including Apache Spark (PySpark), Apache Drill, and GPU accelerated parallel computing frameworks and learn how to apply these techniques to extremely large datasets.

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Cyber Defense Analysis
  • Training, Education, and Awareness

Specialty Areas have been removed from the NICE Framework. With the recent release of the new NICE Framework data, updates to courses are underway. Until this course can be updated, this historical information is provided to give better context as to how it can help you with your cybersecurity goals.

Feedback

If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov(link sends email). Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.

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