Digital Forensics and Machine Learning

Catalog description

This course will provide an overview of digital forensics investigation process with practical hands-on labs and exercises. Course includes labs and assignments where machine learning concepts will be applied, and students will learn the basics of digital forensics techniques and how machine learning could be used in the context of processing data. Note: This course is a cross-leveled course with CSCI-4540. For Master’s level programs, no more than 12 credits of didactic courses required for the program may be in cross-leveled courses. Students are ineligible to take the MS cross-leveled course if they took the undergraduate version previously. Graduate students are expected to write a publishable scholarly paper about digital forensics using machine learning that is beyond what would be expected of undergraduate students. Prerequisite(s): CSCI 3271 >= C or CSCI 3370 >= C and MATH 3280 >= C Lecture Hours: 3 Repeatability: May not be repeated for credit. Grade Mode: Normal, Audit College Restrictions: School of Comp & Cyber Science Course Level Restrictions: Graduate Semester Schedule Type (Primary): Lecture Schedule Type (Additional): Asynchronous Instruction Click here for the Schedule of Classes.