Computer Science B.S. - Data Science
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; Data Science Concentration
Course Requirements
| Code | Title | Hours |
|---|---|---|
| Computer Science Core Courses | ||
| 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 315E | Computers, Ethics, and Society (fulfills the Advanced Writing Requirement) | 3 |
| CSCI 332 | Advanced Data Structures and Algorithms | 3 |
| CSCI 340 | Database Design | 3 |
| CSCI 406 | Careers in Computer Science | 1 |
| M 171 | Calculus I | 4 |
| M 225 | Introduction to Discrete Mathematics | 3 |
| Communication Requirement | ||
| COMX 111A | Introduction to Public Speaking | 3 |
| Data Science Concentration Required Courses | ||
| Complete all of the following courses: | ||
| M 172 | Calculus II | 4 |
| M 221 | Introduction to Linear Algebra | 4 |
| STAT 342 | Probability and Simulation | 3 |
| CSCI 444 | Data Visualization | 3 |
| CSCI 447 | Machine Learning | 3 |
| CSCI 477 | Simulation | 3 |
| Upper-Division Computer Science Electives | ||
| Complete at least 18 credits of Computer Science (CSCI) courses numbered 300 and above, including one course from the approved upper-division math elective courses list below. 1 | 18 | |
Approved upper-division math elective courses: | ||
| Multivariable Calculus | ||
| Introduction to Differential Equations | ||
| Numerical Analysis | ||
| Statistical, Dynamical, and Computational Modeling | ||
| Data Science Analytics | ||
| Total Hours | 74 | |
Four Year Plan
| Freshman | ||
|---|---|---|
| Autumn | Hours | |
| CSCI 150 | Introduction to Computer Science | 3 |
| CSCI 106 | Careers in Computer Science | 1 |
| COMX 111A | Introduction to Public Speaking | 3 |
| General Education Requirement | 6 | |
| Hours | 13 | |
| Spring | ||
| CSCI 151 | Interdisciplinary Computer Science I | 3 |
| WRIT 101 | College Writing I | 4 |
| M 121 |
College Algebra (if needed) 1 or College Trigonometry or Precalculus |
3-4 |
| General Education Requirement | 6 | |
| Hours | 16-17 | |
| Sophomore | ||
| Autumn | ||
| CSCI 152 | Interdisciplinary Computer Science II | 3 |
| M 171 | Calculus I | 4 |
| CSCI 258 | Web Application Development | 3 |
| Lab Science seq I | 4-5 | |
| Hours | 14-15 | |
| Spring | ||
| CSCI 232 | Intermediate Data Structures and Algorithms | 4 |
| M 225 | Introduction to Discrete Mathematics | 3 |
| CSCI 444 | Data Visualization | 3 |
| Lab Science seq II | 4-5 | |
| General Education Requirement | 3 | |
| Hours | 17-18 | |
| Junior | ||
| Autumn | ||
| CSCI 332 | Advanced Data Structures and Algorithms | 3 |
| CSCI 340 | Database Design | 3 |
| M 172 | Calculus II | 4 |
| Science Elective | 3-5 | |
| Intermediate Writing Course | 3 | |
| Hours | 16-18 | |
| Spring | ||
| CSCI 315E | Computers, Ethics, and Society | 3 |
| CSCI 447 | Machine Learning | 3 |
| M 221 | Introduction to Linear Algebra | 4 |
| Science Elective | 3-5 | |
| General Education Requirement | 3 | |
| Hours | 16-18 | |
| Senior | ||
| Autumn | ||
| CSCI 477 | Simulation | 3 |
| STAT 342 | Probability and Simulation | 3 |
| CS Core Elective | 6 | |
| General Education Requirement | 3 | |
| Hours | 15 | |
| Spring | ||
| BMIS 482 |
Big Data Project (Data Science Applications Elective) or Software Design & Development I and Software Design and Development II or Research or Internship or Data Science Projects |
3 |
| M 273 |
Multivariable Calculus (Advanced Math Elective) or Introduction to Differential Equations or Numerical Analysis or or Data Science Analytics |
3-4 |
| CS Core Elective | 6 | |
| General Education Requirement | 3 | |
| Hours | 15-16 | |
| Total Hours | 122-130 | |
Last updated Autumn 2024
- 1
Preparatory course - no credit towards degree, must be taken at this time to assure progression through degree
- 2
M 162 will not be accepted for this concentration