The mathematical sciences have long provided the proper language of the physical sciences and engineering, and they are playing an increasingly important role in areas as diverse as data science, computer science, the social sciences, business administration and economics, and the biological and medical sciences. Many are drawn to the study of mathematics and statistics precisely because of this broad applicability. Others are attracted by the rigorous training these disciplines provide in abstract reasoning, and the many surprising results and elegant arguments they encounter. The department offers a wide variety of courses in mathematics and statistics to meet the needs of a student body having very diverse interests. Anyone who would like to learn more about the department’s faculty, programs, courses, activities and other services is encouraged to explore the department website, or visit the department office.
B.S. in Data Science
The degree program requires a basic core of courses (61 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 |
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| Mth 271 | Mathematical Computing | 4 |
| | or | |
| CS 161 | Introduction to Programming and Problem-Solving | 4 |
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| 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 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:
Approved electives from other disciplines are:
| Actg 335 | Accounting Information Systems and Analytic Fundamentals | 4 |
| Comm 389U | Ethics of Human Communication | 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 | Introduction to Health Informatics | 4 |
| PHE 450 | Epidemiology | 4 |
| Phl 314U | Computer Ethics | 4 |
Total Credit Hours: 73-76
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.