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; CONCENTRATION IN DATA SCIENCE
Course Requirements
| Code | Title | Hours |
|---|---|---|
| Computer Science Core Courses | ||
| Complete all of the following courses: | ||
| CSCI 106 | Careers in Computer Science | 1 |
| 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 |
| M 171 | Calculus I | 4 |
| M 225 | Introduction to Discrete Mathematics | 3 |
| Science Core | ||
| Rule: Complete 1 of the following subcategories of science sequences. 9-10 total credits required. | 9-10 | |
Biology Sequence Option | ||
| Principles of Living Systems | ||
| Principles of Living Systems Lab | ||
| Principles of Biological Diversity | ||
| Principles of Biological Diversity Lab | ||
Chemistry Sequence Option | ||
| College Chemistry I | ||
| College Chemistry I Lab | ||
| College Chemistry II | ||
| College Chemistry II Lab | ||
Physics Sequence Option | ||
| Fundamentals of Physics with Calculus I | ||
| Physics Laboratory I with Calculus | ||
| Fundamentals of Physics with Calculus II | ||
| Physics Laboratory II with Calculus | ||
| Science Electives | ||
| Complete two of the following courses. Laboratory courses must be taken in conjunction with their associated lecture course. The Biology, Chemistry, or Physics sequence chosen to fulfill the science core may not count toward the science electives requirement. | 6-10 | |
| Planetary Astronomy and Planetary Astronomy Lab | ||
| Stars, Galaxies, and the Universe and Stars, Galaxies, and the Universe Lab | ||
| Principles of Living Systems and Principles of Living Systems Lab | ||
| Principles of Biological Diversity and Principles of Biological Diversity Lab | ||
| Microbiology for Health Sciences and Microbiology Health Sciences Lab | ||
| College Chemistry I and College Chemistry I Lab | ||
| College Chemistry II and College Chemistry II Lab | ||
| Forest Biometrics | ||
| Introduction to Physical Geology and Introduction to Physical Geology Lab | ||
| Fundamentals of Physics with Calculus I and Physics Laboratory I with Calculus | ||
| Fundamentals of Physics with Calculus II and Physics Laboratory II with Calculus | ||
| Modern Physics | ||
| Advanced Physics Lab | ||
| Communication Requirement | ||
| Complete one of the following courses: | 3 | |
| Introduction to Public Speaking | ||
| Argumentation | ||
| Data Science Concentration Required Courses | ||
| Complete all of the following courses: | ||
| M 172 | Calculus II | 4 |
| M 221 | Introduction to Linear Algebra | 4 |
| CSCI 444 | Data Visualization | 3 |
| CSCI 447 | Machine Learning | 3 |
| CSCI 477 | Simulation | 3 |
| STAT 342 | Probability and Simulation | 3 |
| Data Science Concentration Advanced Math Elective | ||
| Complete one of the following courses: | 3 | |
| Multivariable Calculus | ||
| Introduction to Differential Equations | ||
| Numerical Analysis | ||
| Statistical, Dynamical, and Computational Modeling | ||
| Data Science Analytics | ||
| Data Science Concentration Data Science Applications Elective | ||
| Complete one of the following courses: | 3-6 | |
| Big Data Project | ||
| Software Design & Development I and Software Design and Development II | ||
| Research 1 | ||
| Internship 2 | ||
| Data Science Projects | ||
| Data Science Concentration Upper-Division Computer Science Elective | ||
| Complete 9-12 credits of CSCI courses numbered 300 and above or a second upper-division Advanced Math Elective. | 9-12 | |
| Total Hours | 86-97 | |
- 1
A maximum of 3 credits of Computer Science electives may be in research credits (CSCI 390 or CSCI 490).
- 2
A maximum of 3 credits of Computer Science electives may be in internship credits (CSCI 398 or CSCI 498).