BIT-4624: Cybersecurity Analytics for Business
Description: Application of advanced analytics to cybersecurity in a business setting. Categorization of cyber threats and solutions. Data mining, visualization and machine learning applied to large data sets for anomaly detection, threat prediction, and incident response analysis. Investigation of adversarial machine learning. Selection of appropriate analytics techniques and security platforms. Consideration of business and ethical issues.
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 19
Average GPA: 3.51 (rounds to A-)
Strict A Rate (No A-) : 50.25%
Average Withdrawal Rate: 0.18%
| Laura M Hodsden | 2024 | 85.5% | 9.9% | 3.1% | 0.0% | 1.6% | 0.0% | 3.75 | 4 |
| Idris Adjerid | 2024 | 53.7% | 38.7% | 5.8% | 0.1% | 1.3% | 0.4% | 3.41 | 9 |
| Michael E Flora | 2024 | 74.8% | 17.3% | 5.8% | 1.7% | 0.4% | 0.0% | 3.60 | 5 |
| Jason J Jacobs | 2022 | 50.0% | 30.0% | 0.0% | 0.0% | 20.0% | 0.0% | 2.96 | 1 |