# 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 |

Mth 271 | Mathematical Computing | 4 |

or | ||

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 350 | Algorithms and Complexity | 4 |

CS 486 | Introduction to Database Management Systems | 4 |

### Additional requirements chosen from approved list of electives

Mth/Stat (two) | Approved 400-level Mth or Stat courses | 6-7 |

Other (two) | Approved 300- or 400-level courses | 6-8 |

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 | Introduction to Health Informatics | 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: 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.