Threat Hunting Techniques
Detect hidden threats with data science and ML-based hunting
Learn how to uncover hidden threats by combining data science, machine learning, and security analytics. Explore hands-on techniques for parsing logs, visualizing data, and running advanced hunts using Splunk, Jupyter, and popular Python tools. Build practical skills for proactive threat detection in modern environments.
Starweaver | Jun 2026 | 266 min
What You Will Learn
You will move step by step from understanding threat hunting concepts to applying data science workflows. Each section builds on the last, guiding you through log preparation, visualization, machine learning, and full hunt execution. Interactive labs in Splunk and Jupyter help you turn theory into real investigative skills.
Key Features
- Map threats using MITRE ATT&CK and develop effective hunt strategies
- Clean, analyze, and visualize security logs with Pandas, Seaborn, and Matplotlib
- Apply machine learning techniques like Isolation Forest and DBSCAN for anomaly detection
Target Audience
This course is ideal for SOC analysts, threat hunters, blue team engineers, and cybersecurity students ready to move beyond basic alert triage. If you want hands-on experience with Splunk, Jupyter, log analysis, and machine learning for proactive defense, you'll find the content practical and directly applicable to your work.
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