SANS – SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals 2022-6

Updated August 10, 2026 108 MB

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Description

SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals. This course teaches professionals the practical skills needed to design and build AI-based security solutions. Focusing on the practical application of machine learning in security, the course spends over seventy percent of its time conducting hands-on labs, transforming complex concepts into accessible tools. Rather than focusing on pure theory, participants will go directly to solving real-world security challenges using statistical models, probabilistic tools, and neural networks. They will acquire key skills such as mining, analyzing, and visualizing security data, building predictive models for threat detection, and implementing anomaly detection systems. The curriculum strikes an optimal balance between theoretical foundations and practical application, requiring only an intermediate knowledge of Python and basic mathematics. This course prepares professionals for the GMLE certification exam and teaches techniques that can be used immediately to improve security operations, incident response, and threat hunting within an organization.

What you will learn

Designing Custom Machine Learning Solutions for Data Security: Participants will learn how to design machine learning solutions tailored to their security needs.
Implementing Anomaly Detection and Threat Hunting Based on Artificial Intelligence: They will gain the ability to implement systems to detect anomalies and hunt threats using artificial intelligence.
Building Neural Networks: Learn how to build neural networks for security classification tasks.
Creating Effective Visualizations: Participants will learn how to create effective visualizations to display security insights.
Automation Development with Python: Acquire skills in automating security data analysis using the Python programming language.
Reducing false alarms: Learn how to reduce the number of false alarms.
Improved threat detection: Enhance threat detection capabilities with AI predictive capabilities.
Automate Security Tasks: Learn how to automate routine security tasks through machine learning.
Detecting undetectable anomalies: They can detect security anomalies that were previously undetectable.
Resource Optimization: Optimize security resource allocation using data insights.
Improve incident response time: Improve incident response time with intelligent analytics.
Strengthening the security posture: Strengthening the organization’s security posture with proactive AI detection.

This course is suitable for people who:

Information security professionals who want to learn about machine learning.
Professionals who are interested in applying data science principles to real-world problems.
Anyone who has tried to learn the basics but can’t turn their problem into something that can be solved with machine learning.
Blue team and SOC members who seek to identify anomalies and perform custom threat hunting.

Course Description SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals

Publisher: SANS
Instructor: David Hoelzer
Training level: Beginner to advanced
Training duration: 40 hours and 55 minutes
Number of lessons: 5

Course headings

SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals

Course Prerequisites SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals

Intermediate Python programming skills are essential for this course. While not required, basic knowledge of statistics and mathematics at a pre-calculus level will be beneficial. Students should have a fundamental understanding of cybersecurity concepts and be familiar with common security tools and data sources. No prior experience with machine learning or data science is necessary.