FENS - PYL (202401)

Introduction to Data Analytics

Applied Statistics
This course covers the major topics of descriptive and inferential statistics. Course content includes the basic procedures of choosing and conducting appropriate statistical tests for a given research or business problem. This is primarily a lecture course, with a fair amount of in-class and out of class coding work using Python. Students should gain a strong foundation in inferential statistics, including z-tests, t-tests, ANOVA, Chi-Square, Linear Regression and other Non-Parametric tests used in assessing the presence of an effect under investigation. Students will understand the theory behind these methods, and be able to apply them correctly and appropriately to analyze and infer from data, and be able to interpret the results.

Intr.to Data Mod.and Process.

Modeling and Optimization

Graduate Seminar I

Graduate Seminar II

Int. to Crypto.&Sec.Protocols

Network Security

Malware Analysis and Detection

Cybersecurity Practices & App.

Graduate Seminar I

Graduate Seminar II

PhD Dissertation