• Lecture time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Lab time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Domain: Insurance
  • Keywords: abnormality, Security, Unsupervised, Visualizations
  • Tools: Machine Learning, Pandas, Python, SQL
  • Citizenship: Open to all students
Summary

In the normal course of business, the security programs amount a staggering sum of data. Sifting through this data to discover irregular issues for devices, users, and logs is difficult and unwieldy. Author a framework capable of making these discoveries and detections.

Description

Please see the PDF for a detailed project description. When registering for this project in UniTime, look for 'Elevance' in the Note section, and select the appropriate CRN.