Curriculum and Course Sequence

The master of science in data science at Elmhurst requires the successful completion of 10 courses for a total of 30 semester hours (7.50 credits).

Students complete two project-based courses, providing an environment for integrating lessons learned from the program’s multi-faceted approach and for refining skills necessary to put the program’s theoretical knowledge to work in realistic and changing circumstances.

Required Courses

  • MDS 546 Quantitative Methods
  • MDS 523 Data Warehousing
  • MDS 534 Data Mining and Business Intelligence
  • MDS 549 Data Mining Project
  • MDS 535 Programming Languages and Environments
  • MDS 556 Analytical Methods
  • MDS 564 Advanced Data Mining and Analytics
  • MDS 576 Research Methods in Data Science
  • Two graduate-level electives

Program Format

  • A part-time program that can be completed in two years
  • Fully online, with classes that are flexible enough to accommodate the schedules of professionals with work and family commitments
  • Students complete coursework through eight-week sessions

Sample Course Sequence

Fall A

  • MDS 546 Quantitative Methods

Fall B

  • MDS 523 Data Warehousing

Spring

  • MDS 534 Data Mining and Business Intelligence

Spring B

  • Elective

Summer

  • MDS 549 Data Mining Project

Fall A

  • MDS 535 Programming Language and Environment

Fall B

  • MDS 556 Analytical Methods

Spring A

  • MDS 564 Advanced Data Mining and Analytics

Spring B

  • Elective

Summer

  • MDS 576 Research Methods in Data Science

Elmhurst College reserves the right to modify courses, schedules and program format without advance notice to students.

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