SKILL BENCHMARK

Predictive Analytics in Cybersecurity Competency (Intermediate Level)

  • 15m
  • 15 questions
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The Predictive Analytics in Cybersecurity Competency (Intermediate Level) benchmark measures your ability to apply machine learning and predictive analytics techniques to identify and prevent cyber attacks. You will be evaluated on your skills in identifying and testing network cyber attack data, visualizing data, setting up data for machine learning, and preprocessing and transforming data before applying machine learning techniques, classification models, and feature selection. A learner who scores high on this benchmark demonstrates that they have experience in applying machine learning and predictive analytics for cybersecurity with minimal supervision.

Topics covered

  • create a column for the cyberattack type
  • perform feature selection for the cyberattack classification model
  • perform one-hot encoding on cyberattack data and view the results
  • predict cyberattacks by performing feature selection on a model
  • predict cyberattacks using heatmap and pie charts
  • read in a network attack detection dataset to pandas
  • select features for the model using the chi-square test
  • set up cyberattack data for machine learning (ML)
  • set up data for cyberattack type classification
  • test the performance of an overfit attack classification model and select some features from the data
  • train the attack type classification model and view the results on the in-sample validation data
  • use a chi-square test to perform feature selection
  • view the performance of an overfit cyberattack prediction model
  • view the training and testing datasets for identifying cyberattacks
  • visualize network cyberattack data and view the unique values