Computer Science-Mathematical Sciences B.S. (Combined Major)
The purpose of the combined program is to provide a thorough background in both allied disciplines and to inculcate a deeper understanding of their goals and methods. A student must complete 62 credits in the two disciplines:
- 31 of these credits in Computer Science courses and
- 31 of these credits in Mathematical Sciences courses.
Each student plans a program in consultation with a Computer Science and a Mathematical Sciences advisor. Students planning to attend graduate school in computer science or the mathematical sciences should consult with their respective advisors.
General Degree Requirements
To earn a baccalaureate degree, all students must complete successfully, in addition to any other requirements, the University of Montana General Education Requirements. Please refer to the General Education Requirements page for more information.
Additional requirements for graduation can be found on the Degree/Certificate Requirements for Graduation page.
Unless otherwise noted in individual program requirements, a minimum grade point average of 2.00 in all work attempted at the University of Montana-Missoula is required for graduation. Please see the Academic Policies and Procedures page for information on how your GPA is calculated.
Courses taken to satisfy the requirements of a major, minor, or certificate program must be completed with a grade of C- or better unless a higher grade is noted in the program requirements.
Bachelor of Science - Computer Science-Mathematical Science
Course Requirements
| Code | Title | Hours |
|---|---|---|
| Mathematical Sciences Core | ||
| Complete all of the following courses: | ||
| M 171 | Calculus I | 4 |
| or M 181 | Honors Calculus I | |
| M 172 | Calculus II | 4 |
| or M 182 | Honors Calculus II | |
| M 221 | Introduction to Linear Algebra | 4 |
| M 273 | Multivariable Calculus | 4 |
| M 307 | Introduction to Abstract Mathematics | 3 |
| or M 225 | Introduction to Discrete Mathematics | |
| Mathematical Sciences Electives 1 | ||
| Complete 12 credits of the following courses: | 12 | |
| Introduction to Differential Equations | ||
| Discrete Mathematics | ||
| Number Theory | ||
| Discrete Optimization | ||
| Linear Optimization | ||
| Advanced Calculus I | ||
| Partial Differential Equations | ||
| Deterministic Models | ||
| History of Mathematics | ||
| Abstract Algebra I | ||
| Abstract Algebra II | ||
| Euclidean and NonEuclidean Geometry | ||
| Numerical Analysis | ||
| Statistical, Dynamical, and Computational Modeling | ||
| Data Science Analytics | ||
| Theoretical Basics of Big Data Analytics and Real Time Computation Algorithms | ||
| Introduction to Complex Analysis | ||
| Introduction to Real Analysis | ||
| Graph Theory | ||
| Probability and Simulation | ||
| Probability Theory | ||
| Mathematical Statistics | ||
| Statistical Methods I | ||
| Statistical Methods II | ||
| Computer Science Core | ||
| Complete all of the following courses: | ||
| CSCI 150 | Introduction to Computer Science | 3 |
| CSCI 151 | Interdisciplinary Computer Science I | 3 |
| CSCI 152 | Interdisciplinary Computer Science II | 3 |
| CSCI 232 | Intermediate Data Structures and Algorithms | 4 |
| CSCI 258 | Web Application Development | 3 |
| CSCI 332 | Advanced Data Structures and Algorithms | 3 |
| CSCI 340 | Database Design | 3 |
| Computer Science Electives 2 | ||
| Complete 9 credits of upper-division (300-level or higher) CSCI courses. | 9 | |
| Public Speaking Requirement | ||
| Complete the following course: | ||
| COMX 111A | Introduction to Public Speaking | 3 |
| Total Hours | 65 | |
- 1
The combined 9 credits of Computer Science Electives and twelve 12 credits of Mathematical Sciences Electives must include at least three 3 or 4 credit courses numbered 400 or above, with at least one chosen from each department (not including M 429 and STAT 451, STAT 452).
- 2
A total of at most three of the 9 credits of Computer Science Electives may be in CSCI 398 or CSCI 498.
Four Year Plan
| Freshman | ||
|---|---|---|
| Autumn | Hours | |
| CSCI 106 | Careers in Computer Science | 1 |
| CSCI 150 | Introduction to Computer Science 1 | 3 |
| M 171 | Calculus I 2 | 4 |
| WRIT 101 or COMX 111A |
College Writing I or Introduction to Public Speaking |
3-4 |
| General Education Requirement | 3 | |
| Hours | 14-15 | |
| Spring | ||
| CSCI 151 | Interdisciplinary Computer Science I 1 | 3 |
| M 172 | Calculus II | 4 |
| COMX 111A or WRIT 101 |
Introduction to Public Speaking or College Writing I |
3-4 |
| General Education Requirement | 6 | |
| Hours | 16-17 | |
| Sophomore | ||
| Autumn | ||
| CSCI 152 | Interdisciplinary Computer Science II | 3 |
| CSCI 258 | Web Application Development | 3 |
| M 225 or M 307 |
Introduction to Discrete Mathematics or Introduction to Abstract Mathematics |
3 |
| BIOB 160 & BIOB 161N |
Principles of Living Systems or Principles of Biological Diversity and Principles of Biological Diversity Lab or College Chemistry I and College Chemistry I Lab or College Chemistry II and College Chemistry II Lab or Fundamentals of Physics with Calculus I and Physics Laboratory I with Calculus or Fundamentals of Physics with Calculus II and Physics Laboratory II with Calculus |
4-5 |
| Hours | 13-14 | |
| Spring | ||
| CSCI 232 | Intermediate Data Structures and Algorithms | 4 |
| M 273 | Multivariable Calculus | 4 |
| BIOB 160 & BIOB 161N |
Principles of Living Systems or Principles of Biological Diversity and Principles of Biological Diversity Lab or College Chemistry I and College Chemistry I Lab or College Chemistry II and College Chemistry II Lab or Fundamentals of Physics with Calculus I and Physics Laboratory I with Calculus or Fundamentals of Physics with Calculus II and Physics Laboratory II with Calculus |
4-5 |
| Elective | 2 | |
| Hours | 14-15 | |
| Junior | ||
| Autumn | ||
| CSCI 332 | Advanced Data Structures and Algorithms | 3 |
| M 221 | Introduction to Linear Algebra | 4 |
| General Education Requirement | 3 | |
| Elective | 6 | |
| Hours | 16 | |
| Spring | ||
| CSCI 340 | Database Design | 3 |
| M 325 |
Discrete Mathematics (Math Elective 300+) or Number Theory or Discrete Optimization or Linear Optimization or Advanced Calculus I or Partial Differential Equations or Deterministic Models or History of Mathematics or Abstract Algebra I or Abstract Algebra II or Euclidean and NonEuclidean Geometry or Numerical Analysis or Statistical, Dynamical, and Computational Modeling or Data Science Analytics or Theoretical Basics of Big Data Analytics and Real Time Computation Algorithms or Introduction to Complex Analysis or Introduction to Real Analysis or Graph Theory or Probability and Simulation or Probability Theory or Mathematical Statistics or Statistical Methods I or Statistical Methods II |
6 |
| General Education Requirement | 3 | |
| Elective | 3 | |
| Hours | 15 | |
| Senior | ||
| Autumn | ||
| CSCI Elective 300+ | 6 | |
| M 325 |
Discrete Mathematics (Math Elective 300+) or Number Theory or Discrete Optimization or Linear Optimization or Advanced Calculus I or Partial Differential Equations or Deterministic Models or History of Mathematics or Abstract Algebra I or Abstract Algebra II or Euclidean and NonEuclidean Geometry or Numerical Analysis or Statistical, Dynamical, and Computational Modeling or Data Science Analytics or Theoretical Basics of Big Data Analytics and Real Time Computation Algorithms or Introduction to Complex Analysis or Introduction to Real Analysis or Graph Theory or Probability and Simulation or Probability Theory or Mathematical Statistics or Statistical Methods I or Statistical Methods II |
3 |
| Elective | 6 | |
| Hours | 15 | |
| Spring | ||
| M 325 |
Discrete Mathematics (Math Elective 300+) or Number Theory or Discrete Optimization or Linear Optimization or Advanced Calculus I or Partial Differential Equations or Deterministic Models or History of Mathematics or Abstract Algebra I or Abstract Algebra II or Euclidean and NonEuclidean Geometry or Numerical Analysis or Statistical, Dynamical, and Computational Modeling or Data Science Analytics or Theoretical Basics of Big Data Analytics and Real Time Computation Algorithms or Introduction to Complex Analysis or Introduction to Real Analysis or Graph Theory or Probability and Simulation or Probability Theory or Mathematical Statistics or Statistical Methods I or Statistical Methods II |
3 |
| CSCI Elective 300+ | 3 | |
| Elective | 9 | |
| Hours | 15 | |
| Total Hours | 118-122 | |
Last updated Autumn 2024