| Statistics and Data Science Program: 48 Credit Hours |
| Compulsory Courses: 36 Credit Hours |
| Course Code |
Course Title |
Theoretical |
Practical |
Credit Hours |
Prerequisite |
| SDS311 |
Probability Theory |
2 |
2 |
3 |
STA211 |
| SDS321 |
Distribution Theory |
2 |
2 |
3 |
STA211 |
| SDS322 |
Numerical Analysis |
2 |
2 |
3 |
STA111 |
| SDS411 |
Mathematical Statistics |
2 |
2 |
3 |
-- |
| SDS412 |
Econometrics |
2 |
2 |
3 |
STA211 |
| SDS413 |
Linear Algebra |
2 |
2 |
3 |
STA111 |
| SDS414 |
Advanced Math |
2 |
2 |
3 |
STA111 |
| SDS415 |
Estimation Theory |
2 |
2 |
3 |
-- |
| SDS421 |
Theory of Statistical Hypothesis Testing |
2 |
2 |
3 |
SDS415 |
| SDS422 |
Applied Categorical Data Analysis |
2 |
2 |
3 |
-- |
| SDS423 |
Experimental Design |
2 |
2 |
3 |
-- |
| SDS424 |
Graduation Project |
2 |
2 |
3 |
-- |
| Elective Courses: 12 Credit Hours* |
| SDS312 |
Introduction to SPSS |
2 |
2 |
3 |
--- |
| SDS313 |
Introduction to Programming with R |
2 |
2 |
3 |
--- |
| SDS323 |
Introduction to Nonparametric Statistics |
2 |
2 |
3 |
STA121 |
| SDS324 |
Statistical Quality Control |
2 |
2 |
3 |
STA121 |
| SDS416 |
Introduction to Applied Statistical Computing |
2 |
2 |
3 |
--- |
| SDS417 |
Introduction to Statistical Programming with Python |
2 |
2 |
3 |
--- |
| SDS425 |
Data Mining |
2 |
2 |
3 |
--- |
| SDS426 |
Machine Learning |
2 |
2 |
3 |
--- |
