Area V: Digital Forensic Analysis

Advanced Machine Learning for Security Analytics:

Description: A deep dive into advanced machine learning techniques for security data analysis, including unsupervised learning and deep learning applications.

Learning Objectives: Students will master security-specific ML techniques, such as adversarial machine learning and anomaly detection.

Course Duration: 70 hours

Prerequisites: Advanced machine learning expertise, familiarity with cyber security concepts

Target Audience: Data scientists and cyber security analysts

Digital Forensics with Python:

Description: This course teaches the fundamentals of digital forensics, including data acquisition, analysis, and reporting, with a focus on using Python for forensic investigations.

Learning Objectives: Participants will learn to apply Python to extract and analyse data from various digital sources, including computers and mobile devices.

Course Duration: 40 hours

Prerequisites: Basic Python skills, foundational knowledge of digital forensics

Target Audience: Law enforcement, cyber security professionals, and students interested in forensics

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