Bachelor of Science in Computational Mathematics with Concentration in Data Science

Embry-Riddle Aeronautical University - Daytona Beach Campus

USA,Florida

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48 Months

Duration

CAD 44,324/year

Tuition Fee

CAD 50

Application Fee

Apply Date

USA, Florida

Type: University

Location Type: Urban

Founded: 1926

Total Students: 33,000 +

Campus Detail

Main Campus Address

1 Aerospace Boulevard, Daytona Beach, Florida 32114, USA

Bachelor of Science in Computational Mathematics with Concentration in Data Science

Program Overview

The Bachelor of Science in Computational Mathematics, available at Embry?Riddle's Daytona Beach Campus, provides a solid foundation in the application of mathematics across disciplines that require quantitative analysis. This program, housed in the College of Arts & Sciences, develops strong analytical and problem-solving skills related to computing, mathematics, statistics, and basic science.

All majors in the Computational Mathematics program, regardless of track, are encouraged to engage in industrial research opportunities under the guidance of faculty members. Students enrolled in this interdisciplinary major select the Data Science Track or the Engineering Application Track.

Why pursue a degree in Computational Mathematics?

The Computational Mathematics degree, housed in the Department of Mathematics, prepares students for applied mathematics careers that require highly developed critical-thinking and problem-solving skills.
What does computational mathematics coursework include?

This program emphasizes the use of computers as tools to solve mathematically modeled real-world and data-enabled problems. This program also features project-based learning as students work on real-world problems provided directly by business and industry. This experience provides students with many opportunities for internships and undergraduate research, which further bolster employment prospects.

Student Learning Outcomes

Students will:

  • Orally communicate mathematical ideas effectively.
  • Use mathematical libraries, packages, or software to solve scientific problems.
  • Use numerical techniques to solve applied problems.
  • Use theoretical foundations of statistics to analyze data sets.
  • Work effectively in teams to solve scientific problems with significant mathematical content.
  • Prepare written scientific project reports to communicate mathematical ideas effectively.