Program Overview

Data science is a rapidly growing field with a wide variety of applications. Different aspects of the data science project lifecycle include the acquisition and preparation of data, followed by the development, testing, and revision of a model, and finishing with the interpretation and implementation of the results. Data science is also closely related to and overlaps with AI and machine learning, which are at the forefront of academia, industry, and society.

Curriculum Requirements - Total Credits Required: 126

First Year - Credits: 32

  • Aesthetic Awareness General Education Requirement (Cr: 3)
  • CSC 105 - AI for All (Cr: 3)
  • CSC 160/160L - Introduction to Programming and Lab (Cr: 4)
    Satisfies the Science and Technology General Education Requirement
  • ENG 111 - Critical Reading and Writing I (Cr: 3)
    Satisfies the Writing Designated Core requirement
  • ENG 112 - Critical Reading and Writing II (Cr: 3)
    Satisfies the Writing Designated Core requirement
  • INT 100 - Internship I (Cr: 2)
  • MTH 134 - Calculus I (Cr: 4)
    Students who do not directly place into MTH 134 will be required to take MTH 129 that can count as a General Education elective
  • MTH 137 - Calculus II (Cr: 4)
    Initial enrollment is based on placement examinations and AP results.  Students placed directly into MTH 137 will be required to replace MTH 134 with a free elective.
  • MTH 146 - Data Science I (Cr: 3)
  • MTH 238 - Linear Algebra (Cr: 3)

Second Year - Credits: 32

  • General Education Elective (Cr: 3)
  • Science and Technology General Education Requirement (Cr: 3)
  • Global Issues General Education Requirement (Cr: 3)
  • CSC 265 - Discrete Structures (Cr: 3)
  • MTH 138 - Introduction to Probability and Statistics in R (Cr: 3)
  • MTH 210 - Mathematical Reasoning (Cr: 3)
  • MTH 237 - Calculus III (Cr: 3)
  • MTH 246 - Data Science II (Cr: 3)
  • MTH 260 - Applied Probability (Cr: 3)
  • MTH 330 - Ordinary Differential Equations (Cr: 3)
  • INT 200 - Internship II (Cr: 2)

Third Year - Credits: 32

  • General Education Elective (3 credits must be above the 100 level) (Cr: 6) 
  • Values and Ethical Reasoning General Education Requirement (Cr: 3)
  • World Cultures General Education Requirement (Cr: 3)
  • CSC 460 - Advanced Topics in Artificial Intelligence (Cr: 3)
  • MTH 316 - Advanced Statistics (Cr: 3)
  • MTH 338 - Applied Linear Algebra for Data Science (Cr: 3)
  • MTH 346 - Advanced Topics in Data Science (Cr: 3)
  • MTH 350 - Mathematical Modeling and Numerical Analysis (Cr: 3)
  • MTH 379 - Semester Internship Strategies (Cr: 1)
  • PHY 201/201L - Physics with Calculus I and Lab (Cr: 4)

Fourth Year - Credits: 30

  • General Education Elective (must be above the 100 level) (Cr: 3) 
  • Individual and Society General Education Requirement  (Cr: 3)
  • Literary Perspectives General Education Requirement   (Cr: 3)
  • Data Science Elective (Cr: 3)
  • MTH 480 - Senior Internship (Cr: 12)
  • MTH 489 - Senior Research (Cr: 3)
  • MTH 490 - Senior Thesis (Cr: 3)

Data Science Electives

Students choose one course from the following list:

  • BEN 345 - Bioinformatics (Cr: 3)
  • CSC 161/161L - Data Structures and Algorithms (Cr: 4)
  • CSC 166 - Rapid Application Development (Cr: 3)
  • CSC 246 - Data and Machine Learning Engineering (Cr: 3)
  • CSC 260 - Object Oriented Programming (Cr: 3)
  • CSC 340 - Databases (Cr: 3)
  • ENV 212 - Introduction to Geographic Information Systems (Cr: 3)
  • MTH 360/360L - Multivariate Probability and Lab (Cr: 4)

Learning Outcomes

At the completion of this program, student will be able to:

  • Describe all components of a data science project from inception to completion
  • Create and execute data science projects using real-world data
  • Analyze the role mathematics plays in predictive tools
  • Program effectively in more than one language/software
  • Address the limitations and uncertainty inherent in data inference 
  • Communicate technical concepts and interpretations to a general audience

View academic catalog and learning outcomes

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