Mathematics, 4+1 BS/ Applied Mathematics, MS
General Requirements
To earn a degree, students must satisfy all requirements in each of the three areas below, in addition to their individual major requirements.
- CU Denver General Graduation Requirements
- CU Denver Core Curriculum
- College of Liberal Arts & Sciences Graduation Requirements
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Program Requirements
While students are completing a BS degree in Mathematics, they may also complete some of the requirements for an MS degree in Applied Mathematics by participating in the BS/MS program using the following guidelines:
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The student must apply and be accepted for participation in the BS/MS program prior to completion of the BS degree in consultation with both the undergraduate and graduate advisors. Students must complete a 4+1 intent form to formally declare this program, as they work very closely with undergraduate and graduate advisors to ensure they are on track and completing requirements as necessary.
- Students should declare their intent to complete this program in their junior or senior year to the Director of the Program in Applied Mathematics after completing MATH 1401 Calculus I, MATH 2411 Calculus II, MATH 2421 Calculus III, MATH 3000 Introduction to Abstract Mathematics, MATH 3191 Applied Linear Algebra, MATH 4310 Introduction to Real Analysis I. A 3.0 grade point average (GPA) is required over all mathematics courses.
- Students must complete a total of 45 credit hours, including a minimum of 42 MATH credit hours.
- Students must complete at least 30 upper-division (3000-level and above) credit hours in the major.
- Students must earn a minimum grade of C- (1.7) in all undergraduate courses that apply to the major and must achieve a minimum cumulative undergraduate major GPA of 2.25. Students must earn a minimum grade of B- (2.7) in all graduate courses and must achieve a minimum cumulative major GPA of 3.0, for all courses that will apply to the MS. Courses taken using P+/P/F or S/U grading cannot apply to major and graduate requirements.
- Students must complete a minimum of 15 upper-division level MATH credit hours and all graduate level credit hours with CU Denver faculty.
- Students must complete a 4+1 intent form to formally declare this program, as they work very closely with undergraduate and graduate advisors to ensure they are on track and completing requirements as necessary. Students must apply and be accepted to the Applied Mathematics, MS during the last semester of their undergraduate career. A maximum of 12 credit hours of graduate level courses that are applied to the undergraduate degree will apply to the graduate degree.
- Students will be advised to take MATH 4320 Introduction to Real Analysis II as an elective for the B.S.
- In the semester in which the student intends to complete their BS, students must apply for admission into MS degree in Applied Mathematics. Students must complete either the requirements for the M.S. degree without concentration area or specific coursework requirements in one of the following areas: Applied Probability, Applied Statistics, Discrete Mathematics, Mathematics of Engineering and Science, Numerical Analysis, or Operations Research.
- The following MATH courses will not count toward a graduate degree: MCKE 5000 Algebraic Patterns and Functions I-MCKE 5009 Math Modeling--Using and Applying Math, MATH 5010 History of Mathematics, MATH 5012 An Advanced Perspective on Number and Operation-MATH 5015 Capstone Course for Secondary Teachers, MATH 5017 Topics in Mathematics for Teachers, MATH 5198 Mathematics for Bioscientists, and MATH 5830 Applied Statistics.
Mathematics, BS Course Requirements
Programming Requirements
| Code | Title | Hours |
|---|---|---|
| Complete one of the following programming requirements: | 3-4 | |
| Programming for Data Science | ||
| Fundamentals of Computing and Fundamentals of Computing Laboratory | ||
Mathematics Courses
| Code | Title | Hours |
|---|---|---|
| Complete all of the following Mathematics courses: | 24 | |
| Calculus I | ||
| Calculus II | ||
| Calculus III | ||
| Introduction to Abstract Mathematics | ||
| Applied Linear Algebra | ||
| Introduction to Real Analysis I | ||
| Statistical Theory | ||
Electives
| Code | Title | Hours |
|---|---|---|
| Complete two approved MATH electives (at least six semester hours) above the 3000 level, excluding MATH 3195, MATH 3511, MATH 3800, MATH 3999, and MATH 4830. | 6 | |
| Elementary Differential Equations | ||
| Introduction to Optimization | ||
| Data Wrangling & Visualization | ||
| Introduction to Symbolic Logic | ||
| Introduction to Probability | ||
| History of Mathematics | ||
| Topics in Mathematics | ||
| Theory of Numbers | ||
| Introduction to Modern Algebra | ||
| Introduction to Real Analysis II | ||
| Intro to Statistical and Machine Learning | ||
| Applied Regression Analysis | ||
| Machine Learning Methods | ||
| Game Theory | ||
| Applied Graph Theory | ||
| Applied Combinatorics | ||
| Complex Variables | ||
| Numerical Analysis I | ||
| Numerical Analysis II | ||
| Partial Differential Equations | ||
| Probabilistic Modeling | ||
MATH numbered 5000 or above
Note that these courses taken during the undergraduate career with be used for the B.S. and apply to the 30 hours of course work and satisfy the core requirement for the Applied Mathematics.
| Code | Title | Hours |
|---|---|---|
| Complete the following: | 12 | |
| Math Clinic | ||
or MATH 6330 | Workshop in Statistical Consulting | |
| Complete nine semester hours of MATH numbered 5000 or above from the list below. | ||
| Applied Analysis | ||
or MATH 6131 | Real Analysis | |
| Functions of a Complex Variable | ||
| Probability | ||
| Statistical Inference | ||
| Applied Regression Analysis | ||
| Game Theory | ||
| Network Flows | ||
| Linear Programming | ||
| Numerical Analysis I | ||
| Numerical Analysis II | ||
| Partial Differential Equations | ||
| Probabilistic Modeling | ||
| Topics in Discrete Math | ||
| Uncertainty Quantification | ||
| Real Analysis | ||
| Stochastic Processes | ||
| Spatial Data Analysis | ||
| Statistical and Machine Learning | ||
| Applied Graph Theory | ||
| Nonlinear Programming | ||
| Introduction to Finite Element Methods | ||
| Research Methods in Mathematics and Statistics | ||