Carnegie Mellon University’s Software Engineering Institute (SEI) has launched the CERT Certificate in Data Science for Cybersecurity. The new program aims to improve the data analysis skills of cybersecurity professionals and help them accomplish security goals.
Focusing on Data in Cybersecurity
The defense acquisition workforce needs to increase capability in using data science to accomplish the many goals it faces, said Thomas Scanlon, technical manager for the CERT Division’s Data Science team. The new program introduces foundational concepts of statistical analysis as a precursor to analyzing data for cybersecurity. SEI instructors teach concepts and techniques to apply data analysis in the context of NetFlow, malware, and digital forensics data. Additionally, students have opportunities to apply what they learn in specifically designed exercises.
What the Program Consists Of
- Fundamental of Statistics Applied to Cybersecurity (6 hours)
- Advanced Analytics—NetFlow (5 hours)
- Advanced Analytics—Malware (5 hours)
- Advanced Analytics—Digital Forensics (6 hours)
- Applied Data Science for Cybersecurity Certificate Examination
Those enrolled in the program have around-the-clock access to the course materials and 24 months in which to complete the coursework and pass the capstone examination. Students earn 2.2 continuing education units (CEUs) after successfully completing the course, which may be accepted for many different types of professional certifications.
Improving Cybersecurity Professionals’ Skills
The CERT Certificate in Data Science for Cybersecurity program is a timely and important addition to the training options available to cybersecurity professionals. SEI’s focus on data and its applications to cybersecurity demonstrates an understanding of the changing nature of cybersecurity threats and the importance of skilled professionals to counter such threats. The flexibility of the program is especially important as it allows working professionals to continue their education without disrupting their work schedule.