Applied Mathematics Data Science Concentration

Curriculum Requirements - Total Credits Required: 127

First Year - Credits: 33

• CSC 160/160L - Introduction to Programming and Lab (Cr: 4)
  
  Satisfies the Science and Technology General Education Requirement

• CSC 161/161L - Data Structures and Algorithms (Cr: 4)
  

• ENG 111 - Critical Reading and Writing I (Cr: 3)
  

• ENG 112 - Critical Reading and Writing II (Cr: 3)
  

• 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 as a Free Elective

• MTH 137 - Calculus II (Cr: 4)
  

• MTH 146 - Data Science I (Cr: 3)
  

• MTH 210 - Mathematical Reasoning (Cr: 3)
  

• MTH 238 - Linear Algebra (Cr: 3)
  

Sophomore - Credits: 32

• General Education Elective (Cr: 3)
• Science and Technology General Education Requirement (Cr: 3)
• Global Issues General Education Requirement (Cr: 3)

• CSC 340 - Database Management (Cr: 3)
  

• MTH 138 - Introduction to Probability and Statistics in R (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)
  

• MTH 338 - Applied Linear Algebra for Data Science (Cr: 3)
  

• INT 200 - Internship II (Cr: 2)
  

Junior - Credits: 32

• General Education Elective (Cr: 6) (One elective must be above the 100 level)
• Aesthetic Awareness General Education Requirement (Cr: 3)
• World Cultures General Education Requirement (Cr: 3)

• CSC 440 - Data Mining and Visualization (Cr: 3)
  

• MTH 316 - Advanced Statistics (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)
  

Senior - Credits: 30

• General Education Elective (Cr: 6) (must be above the 100 level)
• 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:

• BIO 340 - Bioinformatics (Cr: 3)
  
  Or

• BEN 345 - Bioinformatics (Cr: 3)
  

• CSC 260 - Visual Programming I (Cr: 3)
  

• CSC 460 - Introduction to Artificial Intelligence and Machine Learning (Cr: 3)
  

• ENV 212 - Introduction to Geographic Information Systems (Cr: 3)
  

• MTH 346 - Advanced Topics in Data Science (Cr: 3)
  
  (may repeat if different topic)

• 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