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Students in the Mathematics concentration deepen their knowledge of the mathematical underpinnings of data science through courses that include linear algebra, network science, discrete math and probability. The skills learned in this concentration will prepare students for a wide range of employment in data science or for graduate work in data science or statistics.

Required Common Core Courses (38-39 credits)

Level L1 Data Science Foundation

  • MAT 243 Calculus I with Technology
    or MAT 195 Calculus for Business/BIS/Economics
  • MAT 216 Statistical Data Analysis
    or ECO 215 Statistics for Business/Economics
    or MAT 315 Applied Probability and Statistics
    (or an approved statistics course)
  • MAT 342 Explorations in Data Science
  • CSC 202 Introduction to Programming and Machine Intelligence
  • CSC 203 Advanced Programming for Data Science
  • BUS 205 Information Management
  • BUS/BIS 305 Business Analytics
  • EES 300 Introduction to GIS
  • EES 301 Introduction to GIS Laboratory

Level L2 Database Course

  • CSC 341 Database and Information Management
    or BIS 373 Business Database Management

Level L3 Data Mining/Analytics

  • MAT 343 Explorations in Data Analytics
    or CSC 305 Data Mining and Applications
    or BIS 447 Business Intelligence

Level L4 Stage 2 Writing

  • BIS 449 Data Visualization

Level L5 Capstone, Stage 3 Writing, Tier III

  • BIS 377 Organizational Website & Database Management
    or CSC 450 Senior Research
    or LAP 430 Liberal Arts Capstone Colloquium
    or other “approved TIII & W3” courses

B.S. Degree with Concentration in Mathematics (Total: 55 credits)

Core requirements plus additional required course (4 credits)

  • MAT 244 Calculus II with Technology

Electives (12 Credits)

Select four courses from the following:

  • MAT/CSC 230 Discrete Structures
  • MAT 310 Applied Linear Algebra
  • MAT 355 Probability
  • MAT 356 Financial Mathematics
  • MAT 373 Explorations in Mathematical Biology
  • MAT 374 Explorations in Topics (approved topic such as Network Science, Time Series and Forecasting)
  • MAT 408 Independent Study (in approved topic)
  • CSC 315 Bioinformatics Programming and Analysis
  • EES 342 Advanced Geoinformation Systems with Lab
  • Other approved courses
Professor teaching in front of class