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Part 3 · Course

MA103 DATA-DRIVEN MODELING

Mathematical Sciences · 7 versions

Offerings are listed from 2027-1 Fall through 2031-1 Fall.

MA103 DATA-DRIVEN MODELING

  • 4.5 credit hours
  • (BS=0.0, ET=0.0, MA=4.5)
  • Version 2026-2
  • In effect
Scope
This course presents fundamental concepts in data-driven decision-making, using mathematical models to solve real-world, interdisciplinary problems. Students gain experience transforming ill-defined and complex problems into appropriate mathematical models by identifying reasonable and necessary assumptions. The course emphasizes proper interpretation of findings and effective communication of technical concepts to general audiences. The course exercises a wide array of mathematical concepts while nurturing creativity and critical thinking. Specific topics may include data analytics, classification, optimization, matrices, vectors, and continuous/discrete functions. Students use technology to visualize problems, explore potential solutions, and perform time-consuming calculations.
Lessons
56 @ 55 min (4.000 Att/wk)
Labs
8 @ 55 min
Special requirements
None
Disqualifiers
MA153
MA103 version 2026-2 offerings
Term Sections Section size Capacity Enrolled Wait list Seats Closed Details
2027-1 Fall 61 17 1037 1008 0 29 No Hours for 2027-1 Fall
2027-2 Spring 2 18 36 0 0 36 No Hours for 2027-2 Spring
2028-1 Fall 61 18 1098 0 0 1098 No Hours for 2028-1 Fall
2028-2 Spring 2 18 36 0 0 36 No Hours for 2028-2 Spring
2029-1 Fall 61 18 1098 0 0 1098 No Hours for 2029-1 Fall
2029-2 Spring 2 18 36 0 0 36 No Hours for 2029-2 Spring
2030-1 Fall 61 18 1098 0 0 1098 No Hours for 2030-1 Fall
2030-2 Spring 2 18 36 0 0 36 No Hours for 2030-2 Spring