SNS S595 Applied Data Science and Machine Learning for Cybersecurity Professionals - GIAC Machine Learning Engineer GMLE
 
Course Description
This course empowers cybersecurity professionals to apply data science and machine learning techniques to threat detection analysis and security automation. Learners gain practical experience building training and deploying machine learning models that enhance security operations digital forensics and risk management functions across enterprise environments.
 
What You Will Learn
Collect clean and engineer features from security telemetry and operational data
Apply supervised and unsupervised learning techniques for anomaly and threat detection
Build models that reduce alert fatigue and improve detection precision
Evaluate model performance including bias testing validation and explainability
Deploy machine learning pipelines using Python and industry standard frameworks
Integrate machine learning capabilities into SIEM and SOAR workflows
 
Who This Course Is For
This course is designed for cybersecurity professionals SOC analysts security engineers threat hunters incident responders and technical practitioners seeking to apply data science and machine learning to security operations.
 
Hands On Training Experience
Learners complete extensive hands on labs using realistic security data sets. Exercises include developing anomaly detection systems malware classification models and automated pipelines that support operational security use cases.
 
Course Outcomes
Strengthen cyber defense through data driven detection and automation
Predict and identify emerging threats using behavior based modeling
Reduce alert fatigue with intelligent detection systems
Bridge collaboration between security teams and data science functions