Data Science B.S.
The degree program requires a basic core of courses (65 credits) and elective courses (12-15 credits). This structure gives flexibility to the program that allows students to pursue special areas of interest in applications of data science. The program is designed to provide a foundation for more advanced work and/or a basis for employment in business, industry, and government.
Requirements
In addition to meeting the general University degree requirements, the major in data science must complete the following requirements.
Courses
| Mth 231 | Data Science Seminar | 2 |
| Mth 251 | Calculus I | 4 |
| Mth 252 | Calculus II | 4 |
| Mth 253 | Calculus III | 4 |
| Mth 261 | Introduction to Linear Algebra | 4 |
| Mth 271 | Python for Data Science | 4 |
| CS 161 | Introduction to Programming and Problem-Solving | 4 |
| Mth 343 | Applied Linear Algebra | 4 |
| Mth 371 | Large-Scale Data Algorithms | 4 |
| Stat 361 | Introduction to Statistical Methods | 4 |
| Stat 363 | Statistical Computing and Data Visualization in R | 4 |
| Stat 364 | Modern Regression Analysis | 4 |
| Stat 387 | Introduction to Statistical Learning | 4 |
| Stat 409 | Data Science Practicum | 3 |
| CS 250 | Discrete Structures I | 4 |
| | | |
| CS 284 | Algorithmic Thinking | 4 |
| | or | |
| CS 350 | Algorithms and Complexity | 4 |
| | | |
| CS 486 | Introduction to Database Management Systems | 4 |
Additional requirements chosen from approved list of electives
Check with the department for the list of additional courses, including omnibus-numbered courses, which may be approved as electives.
Approved Mth/Stat Electives are:
| Mth 451 | Numerical Calculus I | 3 |
| Mth 452 | Numerical Calculus II | 3 |
| Mth 453 | Numerical Calculus III | 3 |
| Mth 461 | Graph Theory I | 3 |
| Mth 462 | Graph Theory II | 3 |
| Mth 464 | Numerical Optimization I | 3 |
| Mth 465 | Numerical Optimization II | 3 |
| Stat 451 | Applied Statistics for Engineers and Scientists I | 4 |
| Stat 452 | Applied Statistics for Engineers and Scientists II | 3 |
| Stat 461 | Introduction to Mathematical Statistics I | 3 |
| Stat 462 | Introduction to Mathematical Statistics II | 3 |
Approved electives from other disciplines are:
| Actg 335 | Accounting Information Systems and Analytic Fundamentals | 4 |
| CS 430P | Internet, Web, & Cloud Systems | 4 |
| CS 441 | Artificial Intelligence | 4 |
| CS 445 | Machine Learning | 4 |
| G 324 | Data Management and Analysis | 5 |
| GSCM 412 | Introduction to Enterprise Resource Planning Systems | 4 |
| BTA 481 | Blockchain Fundamentals | 4 |
| Mgmt 442 | Human Resources Information Systems & People Analytics | 4 |
| PHE 350 | Health and Health Systems | 4 |
| PHE 427 | Managing Information in Health Services | 4 |
| PHE 450 | Epidemiology | 4 |
| Phl 314U | Computer Ethics | 4 |
| SySc 336U | Networks and Society | 4 |
| SySc 440 | Introduction to Network Science | 4 |
Total Credit Hours: 77-80
All courses used to satisfy the data science major requirements, whether taken in the department or elsewhere, must be graded C-, P, or above, but no more than 4 courses graded P will count toward these requirements. Transfer students majoring in data science are required to take a minimum of 15 credits of PSU upper-division mathematics or statistics courses in residence.