3-Day Training: Applied Data Science and Machine Learning for Cyber Security (Amsterdam, Netherlands – May 6-8, 2019) – ResearchAndMarkets.com

Training: Applied Data Science and Machine Learning for Cyber Security”

training has been added to ResearchAndMarkets.com’s

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 scaleall with a focus on
security related problems.

Participants will learn how to read in data in a variety of common
formats then write scripts to analyze and visualize that data.

Key Learning Objectives

  • Writing scripts to efficiently read and manipulate CSV, XML, and JSON
  • Quickly and efficiently parsing executables, log files, pcap and
    extracting * artifacts from them
  • Making API calls to merge datasets
  • Use the Pandas library to quickly manipulate tabular data
  • Effectively visualizing data using Python
  • Preprocessing raw security data for machine learning and feature
  • Building, applying and evaluating machine learning algorithms to
    identify potential threats
  • Automating the process of tuning and optimizing machine learning models
  • Hunting 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

Prerequisite Knowledge

Students will need to have an understanding of Python.

Hardware / Software Requirements

  • Students should bring a laptop with either:

    • Virtualbox (or VMWare) installed, 6GB of RAM and 10GB of storage.
    • Anaconda and IPython installed.
  • We strongly recommend using the virtual machine we will provide as it
    will give the best student experience.

What Students Will Be Provided With

A preconfigured virtual machine (VM) containing all the software needed
for the class. The VM will also contain:

  • All course slides, notebooks, reference sheets and handouts.
  • Skeleton code examples for in-class exercises

Students will also be provided with access to our website which will
have additional exercises.

For more information about this training visit https://www.researchandmarkets.com/research/bz24x9/3day_training?w=4


Laura Wood, Senior Press Manager
E.S.T Office Hours Call 1-917-300-0470
For U.S./CAN Toll Free Call
For GMT Office Hours Call +353-1-416-8900
Topics: Professional
Development and Training
, IT
, Machine
Learning and Data Mining

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