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Applied Data Science for Cyber Security

Instructed by Charles Givre

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.

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Learn the following key skills:

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.

LEVEL

All skill levels

FORMAT

In person & Live Online

LOCATION

Columbia, MD (East Coast) San Francisco, CA (West Coast)

DURATION

4 days, 32 hours

TARGET AUDIENCE

If you're in network security and have been thinking of getting into data science... this course is for you. However, this course is also designed for data scientist who have wanted to get into Cybersecurity. We teach fundamental to advanced Data Science and how to apply it to Cybersecurity.

Standard Rate

$3750

Requirements

Students should bring a laptop with either: Virtualbox (or VMWare) installed, 6GB of RAM and 10GB of storage. Anaconda and IPython installed.

Prerequisites

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

Why choose the Center for Cyber Security Training

Interactive, classroom-based learning

Subject matter experts

Trusted by US government agencies

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Charles Givre

Charles Givre is a solutions-focused Senior Technical Executive and Data Scientist with more than 20 years of success across the technology, data science, Fintech, education, and cybersecurity industries. His broad areas of expertise include data visualization, analytics, network security, information assurance, strategic planning, big data, business intelligence, software development, and program management. He has held leadership positions at organizations including JP Morgan Chase, Deutsche Bank, Booz Allen Hamilton, and the Central Intelligence Agency (CIA). As VP and Product Owner for Data & Analytics at JP Morgan Chase, he led the product team to develop a next generation cybersecurity analytics platform. Mr. Givre is a published author, regular conference speaker and Project Management Committee (PMC) chair for the Apache Drill project.

Curtis Lambert

Lead Data Scientist and CTO at DataDistillr. Instructor/CTO/curriculum developer at GTK Cyber, and Security Researcher with TS/SCI clearance, full scope polygraph with over 15 years experience supporting DoD missions as a Network Intelligence Analyst (NIA), Data Analyst, and Malware Analyst. Strong record of technical achievements while supporting national and tactical-level missions focused on analytic methodologies, access development and prototype tool development.

The knowledge I gained through this course was substantial. From learning new script writing techniques to understanding big data tools, the instructor covered everything I was hoping for and more!
- Sarah H., Washington, DC

Want more information?

Download the Applied Data Science for Cyber Security course outline now.

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Upcoming Training Sessions

March 16-20, 2020
June 8-12, 2020
September 7-11, 2020

Classes are limited.

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