Requirements
The Mathematics for Programming and Computing program requires 10 distinct courses for at least 30 credits as described below. While a single courses may be used to fulfill more than one requirement, it will only contribute once to the total course count. Finally, at most one course from each of the following groupings may be used to fulfill the minimum course and credit requirement (i.e.: minimum of ten courses and at least 30 credits): Intro Linear Algebra (MATH 320, MATH 340, MATH 341, MATH 375), Intro Differential Equations (MATH 319, MATH 320 or MATH 376), and Intro Probability (MATH/STAT 309 or MATH/STAT 431).
| Code | Title | Credits |
|---|---|---|
| Core Math Requirement (minimum of six distinct MATH courses for at least 18 credits) | ||
| Linear Algebra | 3-5 | |
| Linear Algebra | ||
or MATH 320 | Linear Algebra and Differential Equations | |
or MATH 340 | Elementary Matrix and Linear Algebra | |
or MATH 375 | Topics in Multi-Variable Calculus and Linear Algebra | |
| Intermediate Mathematics Requirement (complete at least one) | 0-6 | |
| Applied Mathematical Analysis and Applied Mathematical Analysis | ||
| Linear Algebra | ||
| Topics in Multi-Variable Calculus and Linear Algebra | ||
| The Theory of Single Variable Calculus | ||
| Introduction to Number Theory | ||
| Advanced Mathematics Requirement (complete one) | 3 | |
| Numerical Analysis | ||
| Analysis I | ||
| Probability Theory | ||
| Mathematical Methods in Data Science | ||
| Linear Algebra II | ||
| Modern Algebra | ||
| Mathematical Logic | ||
| MATH Elective to reach required minimum of six courses for at least 18 credits | 6-12 | |
At least one course must be from: 1 | ||
| Numerical Linear Algebra | ||
| Numerical Analysis | ||
| Analysis I | ||
| Analysis II | ||
| Linear Optimization | ||
| Probability Theory | ||
| Mathematical Methods in Data Science | ||
| Linear Algebra II | ||
| Modern Algebra | ||
| Modern Algebra | ||
| Modern Number Theory | ||
| Fundamentals of Set Theory | ||
| Mathematical Logic | ||
| Stochastic Methods for Biology | ||
| Data-Driven Dynamical Systems, Stochastic Modeling and Prediction | ||
| Analysis of Partial Differential Equations | ||
| Introduction to Fourier Analysis | ||
| Introduction to Measure and Integration | ||
| Introduction to Stochastic Processes | ||
| An Introduction to Brownian Motion and Stochastic Calculus | ||
Select remaining courses from: | ||
| Introduction to Probability and Mathematical Statistics II | ||
| Techniques in Ordinary Differential Equations | ||
or MATH 376 | Topics in Multi-Variable Calculus and Differential Equations | |
| Applied Mathematical Analysis | ||
| Applied Mathematical Analysis | ||
| Applied Dynamical Systems, Chaos and Modeling | ||
| The Theory of Single Variable Calculus | ||
| Introduction to Combinatorial Optimization | ||
| Introduction to the Theory of Probability | ||
| Introduction to Probability and Mathematical Statistics I | ||
| Introduction to Cryptography | ||
| Applied Linear Algebra | ||
| Graphs and Networks in Data Science | ||
| Introduction to Number Theory | ||
| Introduction to Combinatorics | ||
| Programming and Computations Requirement (Four Courses distinct from the above for at least 12 credits) 2 | ||
| COMP SCI 300 | Programming II | 3 |
| COMP SCI 400 | Programming III | 3 |
| Elective 3 | 6-8 | |
| Introduction to Numerical Methods | ||
| Introduction to Combinatorial Optimization | ||
| Introduction to Cryptography | ||
| Introduction to Computational Statistics | ||
| Introduction to Combinatorics | ||
| Numerical Linear Algebra | ||
| Numerical Analysis | ||
| Introduction to Theory of Computing | ||
| Introduction to Optimization | ||
| Linear Optimization | ||
| Advanced Linear Programming | ||
| Matrix Methods in Machine Learning | ||
| Image Processing | ||
| Computational Photography | ||
| Introduction to the Theory and Design of Programming Languages | ||
| Introduction to Artificial Neural Networks | ||
| Introduction to Artificial Intelligence | ||
| Introduction to Computational Geometry | ||
| Computer Graphics | ||
| Medical Image Analysis | ||
| Introduction to Bioinformatics | ||
| Introduction to Algorithms | ||
| Tools and Environments for Optimization | ||
| Introduction to Information Security | ||
| Total Credits | 30 | |
Residence and Quality of Work
- 2.000 GPA on all MATH courses and courses eligible for the major.4
- 2.000 GPA on at least 15 credits of upper level credit in the major.5
- 15 credits in MATH in the major taken on the UW-Madison campus.6
Footnotes
- 1
This course must be distinct from the advanced mathematics requirement.
- 2
Courses below may have prerequisites outside of the requirements for this named option.
- 3
Any MATH course from the elective list above may be used in lieu of any of the following courses.
- 4
This includes any course with a MATH prefix (including those cross-listed with MATH) regardless of major program as well as only those non-MATH course explicitly listed in the tables above.
- 5
This includes any course with a MATH prefix (including those cross-listed with MATH) numbered 307 and above as well as only those non-MATH courses which appear in the tables above and carry the advanced LAS designation.
- 6
This includes only those courses with a MATH prefix (or crosslisted with MATH).
Four-Year Plan
This Four-Year Plan is only one way a student may complete an L&S degree with this major. Many factors can affect student degree planning, including placement scores, credit for transferred courses, credits earned by examination, and individual scholarly interests. In addition, many students have commitments (e.g., athletics, honors, research, student organizations, study abroad, work and volunteer experiences) that necessitate they adjust their plans accordingly. Informed students engage in their own unique Wisconsin Experience by consulting their academic advisors, Guide, DARS, and Course Search & Enroll for assistance making and adjusting their plan.
In general, your four year plan in mathematics should be organized along the following sequence:
- Calculus
- Linear Algebra
- Required Intermediate level course
- Additional intermediate level courses as needed
- Required advanced level course
- Additional advanced level courses
| Freshman | |||
|---|---|---|---|
| Fall | Credits | Spring | Credits |
| MATH 221 | 5 | MATH 222 | 4 |
| Literature Breadth | 3 | Literature Breadth | 3 |
| Communication A | 3 | Ethnic Studies | 3 |
| Foreign Language (if required) | 4 | Foreign Language (if required) | 4 |
| 15 | 14 | ||
| Sophomore | |||
| Fall | Credits | Spring | Credits |
| MATH 2341 | 4 | MATH Required Linear Algebra | 3 |
| Humanities Breadth | 3 | Required Intermediate MATH | 3 |
| Communication B | 3 | Humanities Breadth | 3 |
| Physical Science Breadth | 3 | Physical Science Breadth | 3 |
| Elective | 3 | Elective | 3 |
| 16 | 15 | ||
| Junior | |||
| Fall | Credits | Spring | Credits |
| Intermediate MATH | 3 | Intermediate MATH | 3 |
| COMP SCI 300 | 3 | COMP SCI 400 | 3 |
| Social Sciences Breadth | 3 | L&S Breadth - Social Science | 3 |
| Biological Sciences Breadth | 3 | Biological Sciences Breadth | 3 |
| Elective | 3 | Elective | 3 |
| 15 | 15 | ||
| Senior | |||
| Fall | Credits | Spring | Credits |
| Required Advanced MATH | 3 | Advanced MATH | 3 |
| Elective Programming/Computations Course | 3 | Elective Programming/Computations Course | 3 |
| Social Science Breadth | 3 | Social Science Breadth | 3 |
| Elective | 3 | Elective | 3 |
| Elective | 3 | Elective | 3 |
| 15 | 15 | ||
| Total Credits 120 | |||
- 1
Students should declare the major upon the successful completion of this course