Mathematics Minor
Introduction
Please click here to see Mathematical and Statistical Sciences department information.
These degree requirements are subject to periodic revision by the academic department, and the College reserves the right to make exceptions and substitutions as judged necessary in individual cases. Therefore, the College strongly urges students to consult regularly with their major advisor and CLAS advisor to confirm the best plans of study before finalizing them.
Program Delivery
- This is an on-campus program.
Declaring This Minor
- Please see your advisor.
- Click here to go to information about declaring a major/minor.
General Requirements
Students must satisfy all requirements as outlined below and by the department offering the minor.
- CU Denver General Graduation Requirements
- Click here for information about Academic Policies
Program Requirements
- Students must complete a minimum of 21 MATH credit hours.
- Students must complete a minimum of 9 upper-division (3000-level and above) MATH credit hours.
- Students must earn a minimum grade of C- (1.7) in all major courses taken at CU Denver and must achieve a minimum cumulative minor GPA of 2.0. All graded attempts in required and elective courses are calculated in the minor GPA. Students cannot complete minor or ancillary course requirements as pass/fail.
- Students must complete a minimum 6 MATH upper-division level credit hours with CU Denver faculty.
Program Restrictions, Allowances and Recommendations
- Be aware of no co-credit policies. Here is a non-exclusive list of our most common no co-credit policies: no co-credit between
- MATH 3800 Probability and Statistics for Engineers and MATH 4810 Introduction to Probability,
- MATH 3195 Linear Algebra and Differential Equations and MATH 3200 Elementary Differential Equations,
- MATH 3191 Applied Linear Algebra and MATH 3195 Linear Algebra and Differential Equations,
- MATH 4387 Applied Regression Analysis and MATH 4830 Applied Statistics.
- For slash-listed courses:
- MATH 3440 Introduction to Symbolic Logic/PHIL 3440 Introduction to Symbolic Logic.
- MATH 4408 Applied Graph Theory/CSCI 4408 Applied Graph Theory,
- MATH 4650 Numerical Analysis I/CSCI 4650 Numerical Analysis I, and
- MATH 4660 Numerical Analysis II/CSCI 4660 Numerical Analysis II, one can take either the MATH section or the slash-listed section of the course. Either one count towards the minor in MATH.
Required Courses
| Code | Title | Hours |
|---|---|---|
| Take all of the following Mathematics courses: | 12 | |
| MATH 1401 | Calculus I | 4 |
| MATH 2411 | Calculus II | 4 |
| MATH 2421 | Calculus III | 4 |
Upper-Division Level MATH Electives
| Code | Title | Hours |
|---|---|---|
| Take three upper-division level (3000 level or higher) MATH courses worth three or more credit hours each. | 9 | |
| MATH 3000 | Introduction to Abstract Mathematics | 3 |
| MATH 3041 | Fundamental Mathematics: Algebra, Probability and Data Analysis | 3 |
| MATH 3191 | Applied Linear Algebra | 3 |
| MATH 3195 | Linear Algebra and Differential Equations | 4 |
| MATH 3200 | Elementary Differential Equations | 3 |
| MATH 3210 | Higher Geometry I | 3 |
| MATH 3301 | Introduction to Optimization | 3 |
| MATH 3302 | Simulation in Operations Research | 3 |
| MATH 3376 | Data Wrangling & Visualization | 3 |
| MATH 3382 | Statistical Theory | 3 |
| MATH 3440 | Introduction to Symbolic Logic | 3 |
| MATH 3511 | Mathematics of Chemistry | 4 |
| MATH 3800 | Probability and Statistics for Engineers | 3 |
| MATH 3939 | Internship | 1-3 |
| MATH 4010 | History of Mathematics | 3 |
| MATH 4015 | Capstone Course for Secondary Teachers | 3 |
| MATH 4027 | Topics in Mathematics | 3 |
| MATH 4110 | Theory of Numbers | 3 |
| MATH 4140 | Introduction to Modern Algebra | 3 |
| MATH 4310 | Introduction to Real Analysis I | 3 |
| MATH 4320 | Introduction to Real Analysis II | 3 |
| MATH 4337 | Intro to Statistical and Machine Learning | 3 |
| MATH 4387 | Applied Regression Analysis | 3 |
| MATH 4388 | Machine Learning Methods | 3 |
| MATH 4390 | Game Theory | 3 |
| MATH 4394 | Experimental Designs | 3 |
| MATH 4408 | Applied Graph Theory | 3 |
| MATH 4409 | Applied Combinatorics | 3 |
| MATH 4450 | Complex Variables | 3 |
| MATH 4650 | Numerical Analysis I | 3 |
| MATH 4660 | Numerical Analysis II | 3 |
| MATH 4733 | Partial Differential Equations | 3 |
| MATH 4779 | Math Clinic | 3 |
| MATH 4791 | Continuous Modeling | 3 |
| MATH 4792 | Probabilistic Modeling | 3 |
| MATH 4793 | Discrete Math Modeling | 3 |
| MATH 4794 | Optimization Modeling | 3 |
| MATH 4810 | Introduction to Probability | 3 |
| MATH 4820 | Introduction to Mathematical Statistics | 3 |
| MATH 4830 | Applied Statistics | 3 |
To learn more about the Student Learning Outcomes for this program, please visit our website.