Master of Science in Data Science

The Master's of Science in Data Science degree at Montana State University is interdisciplinary program that draws on courses in three programs: Computer Science, Mathematics, and Statistics. The broad goal is to provide students with foundational training in data analysis, with equal emphasis on the principles of computer science, mathematics, and statistics, and the ability to apply these principles to a range of data-driven problems. More specifically, the learning outcomes for graduates of the program are:

  • Demonstrate knowledge of essential deterministic, randomized and approximation algorithms for data classification and clustering, dimensionality reduction, regression, and optimization.
  • Demonstrate knowledge in the principles and practice of statistical experimental design, statistical inference, and decision theory.
  • Demonstrate the ability to take a real-world data analysis problem, formulate a conceptual approach to the problem, match aspects of the problem to previously learned theoretical and methodological tools, break down the solution into a step-by-step approach, and implement a working solution in a modern software language.
  • Communicate data science problems, analyses, and solutions effectively to both specialists and non-specialists through the use of effective technical writing, presentations, and data visualizations, and teamwork and collaboration.

Program Prerequisites

The prerequisites for the master's degree program in data science consist of the following course work, or their equivalent if a student is coming from another institution.

  1. 3 semesters of Calculus (through Multivariable Calculus M 273) or equivalent
  2. Linear Algebra (M 221) or equivalent
  3. Data Structures and Algorithms (CSCI 232) or equivalent
  4. Methods of Proof (M 242) or Discrete Structures (CSCI 246) or equivalent
  5. Introductory Statistics (STAT 216Q) or equivalent (additional statistics coursework such as Intermediate Statistical Methods (STAT 217) or STAT 401 or STAT 337 and then STAT 511, STAT 512 preferred)
  6. At least three senior level courses in mathematics, statistics, or computer science or equivalent

Program Requirements

The master's degree program in data science requires a total of 30 credits, which is typically satisfied by taking 10 3-credit courses. There are three essential domains in this program: Computer Science, Statistics, and Mathematics. Each student is required to take:

  • At least 2 courses (=6 credits) in each of the three essential domains.
  • The foundational course in each domain

Additionally, students can choose among the following courses:

Required Foundational Courses

CSCI 532Algorithms3
STAT 541Experimental Design3
M 508Mathematics of Machine Learning3

Curriculum for a student with a dominant interest in Computer Science:

Year 1Credits
CSCI 532 - Algorithms3
CSCI 540 - Advanced Database Systems3
CSCI 547 - Machine Learning3
M 441 - Numerical Linear Algebra & Optimization3
STAT 408 - Statistical Computing and Graphical Analysis3
Year Total: 15
Year 2Credits
CSCI 535 - Computational Topology3
CSCI 550 - Advanced Data Mining3
M 508 - Mathematics of Machine Learning3
STAT 511 - Methods of Data Analysis I3
STAT 541 - Experimental Design3
Year Total: 15
Total Program Credits: 30

Curriculum for a student with a dominant interest in Mathematics:

Year 1Credits
CSCI 532 - Algorithms3
CSCI 547 - Machine Learning3
M 441 - Numerical Linear Algebra & Optimization3
M 560 - Methods of Applied Mathematics I3
STAT 408 - Statistical Computing and Graphical Analysis3
Year Total: 15
Year 2Credits
CSCI 535 - Computational Topology3
CSCI 540 - Advanced Database Systems3
M 508 - Mathematics of Machine Learning3
STAT 511 - Methods of Data Analysis I3
STAT 541 - Experimental Design3
Year Total: 15
Total Program Credits: 30

Curriculum for a student with a dominant interest in Statistics:

Year 1Credits
CSCI 532 - Algorithms3
M 441 - Numerical Linear Algebra & Optimization3
STAT 408 - Statistical Computing and Graphical Analysis3
STAT 511 - Methods of Data Analysis I3
STAT 512 - Methods of Data Analysis II3
Year Total: 15
Year 2Credits
CSCI 547 - Machine Learning3
M 508 - Mathematics of Machine Learning3
STAT 536 - Time Series Analysis3
STAT 537 - Multivariate Analysis I3
STAT 541 - Experimental Design3
Year Total: 15
Total Program Credits: 30