| Core Curriculum Courses | ||
| See the Core Curriculum Requirements | 42 | |
| Courses Required in the Major | 27 | |
| MATH 2305 | Discrete Mathematics | 3 |
| MATH 2318 | Linear Algebra | 3 |
| MATH 2320 | Differential Equations | 3 |
| MATH 2413 | Calculus I * | |
| MATH 2414 | Calculus II | 4 |
| MATH 2415 | Calculus III | 4 |
| MATH 402 | Mathematical Statistics I | 3 |
| MATH 403 | Mathematical Statistics II | 3 |
| COSC 1436 | Introduction to Computer Science and Programming | 4 |
| Required Support Courses | 0-4 | |
| Programming Fundamentals II | ||
| Math Concentration Courses | 9 | |
| MATH 334 | Abstract Algebra | 3 |
| MATH 436 | Real Analysis | 3 |
| or MATH 438 | Complex Analysis | |
| or MATH 440 | Topology | |
| MATH 437 | Number Theory | 3 |
| Math Concentration Electives, 6 credit hours: | ||
| In addition to the required courses, 6 hours of Math courses at 300/400 level except MATH 301, 361, 362, 371, 372, 380 | 6 | |
| Additional Electives | 32-36 | |
| A minor or second major is strongly suggested to meet the academic and career interests. Meet a math faculty member to choose a minor or a second major. Students who take PHYS 2425 or PHYS 2426 to satisfy the required support course must take 36sch to satisfy their elective requirements. | ||
| Total Hours | 120 | |
| Core Curriculum Courses | ||
| See the Core Curriculum Requirements | 42 | |
| Required courses in the major, 31 credit hours: | ||
| MATH 2305 | Discrete Mathematics | 3 |
| MATH 2318 | Linear Algebra | 3 |
| MATH 2320 | Differential Equations | 3 |
| MATH 2413 | Calculus I * | |
| MATH 2414 | Calculus II | 4 |
| MATH 2415 | Calculus III | 4 |
| MATH 402 | Mathematical Statistics I | 3 |
| MATH 403 | Mathematical Statistics II | 3 |
| COSC 1436 | Introduction to Computer Science and Programming | 4 |
| COSC 1437 | Programming Fundamentals II | 4 |
| Required Support Courses | 0-4 | |
| Programming Fundamentals II | ||
| Data Science Concentration Courses, 24 credit hours: | ||
| COSC 2336 | Data Structures and Algorithms | 3 |
| CSCI 333 | Applied Data Analytics with Python | 3 |
| CSCI 340 | Database | 3 |
| CSCI 334 | Introduction to Statistical Programming Methods with R | 3 |
| MATH 303 | Introduction to Data Science | 3 |
| MATH 341 | Statistical Modeling | 3 |
| MATH 342 | Mathematics for Machine Learning | 3 |
| MATH 486 | Image Processing with Applications | 3 |
| Data Science Concentration Electives, 6 credit hours: | ||
| 6 hours of math or approved second major courses at 300/400 level except MATH 301, 361, 362, 371, 372, 380 | 6 | |
| Additional Electives, 17-21 credit hours: | 17-21 | |
| Meet a math faculty member for taking electives. | ||
| Total Hours | 120 | |
This courses will satisfy the Core Curriculum Requirements
