Lab Description

Cybersecurity analysts often deal with large volumes of data from multiple sources, making risk analysis a time-consuming and complex task. Manual processing increases the chances of oversight and delays in identifying critical threats. This lab introduces an automated approach to simplify and enhance this workflow.

You will develop a Python-based solution that integrates a local Large Language Model (LLM) to analyze diverse cybersecurity datasets, such as incident reports and user activity logs. By automating the analysis and report generation process, the lab demonstrates how AI can improve efficiency, accuracy, and decision-making in cybersecurity operations.

What You Will Learn

Program Curriculum

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