Course 2015 Advantage Plan Course
Security teams need to make fast, well-supported decisions even when alerts are piling up, evidence is incomplete, and time is limited. AI-Powered SecOps explains how artificial intelligence can help teams work more effectively without replacing human judgment, security controls, or accountability.
Participants follow security data from collection through analysis and response. They learn how AI can help analysts understand activity, reach conclusions supported by evidence, and recommend next steps. SIEM and SOAR platforms provide the data and controlled workflows, while people and policy continue to determine what the system is allowed to do.
Through detection, investigation, threat hunting, and response activities, participants learn to use trustworthy evidence, set clear limits on AI access and authority, and measure whether AI is improving operations. Hands-on exercises use a local AI model and common security tools, but the methods can be applied across platforms. By the end, participants can recognize when AI can help and when human review or traditional automation is the better choice.
In-Person
Online
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Prerequisites
Attendees should have foundational knowledge of networking and cybersecurity. Experience with security logs, alerts, incident response, or a SIEM or SOAR platform is helpful but not required. Basic familiarity with JavaScript Object Notation (JSON) and Linux may make the exercises easier. No prior artificial intelligence, machine learning, data science, or programming experience is required.
Who Should Attend
Cybersecurity analysts, incident responders, threat hunters, detection engineers, security engineers, SIEM and SOAR administrators, security architects, technical managers, and other professionals responsible for security operations, automation, or AI adoption. This is a technical course, but participants do not need to be dedicated SOC specialists.
What You Will Learn
Chapter 1: Engineering the AI SecOps Runtime
Chapter 2: Building Evidence AI Can Trust
Chapter 3: AI-Powered Detection Engineering
Chapter 4: Evidence-Driven AI Investigation
Chapter 5: AI-Guided Response Orchestration
Chapter 6: Evaluating and Improving AI SecOps
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AI-powered security operations use artificial intelligence to help security teams interpret evidence, prioritize alerts, investigate threats, develop detections, and coordinate response. This course teaches how to apply those capabilities while preserving evidence quality, human oversight, and decision authority.
AI is integrated across the security operations lifecycle—from preparing security data and analyzing alerts to building detections, investigating activity, recommending response actions, and measuring results. You will also learn when AI output must be validated, restricted, or escalated for human review.
Yes. You will complete practical exercises using security data and tools such as Wazuh, Zeek, osquery, Sigma, YARA, Shuffle, and a local AI model. The exercises cover data normalization, detection engineering, threat investigation, incident response, and continuous improvement.
This course is designed for SOC analysts, security engineers, incident responders, and other cybersecurity professionals who want to apply AI to security operations. Foundational knowledge of networking, cybersecurity, and security logs is recommended, but advanced AI experience is not required.
