Curriculum and Course Sequence

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

Projects chosen by students form the foundation for most courses, providing an environment for integrating lessons learned and for refining skills necessary to put the program’s theoretical knowledge to work in realistic and changing circumstances.

Required Courses

All students complete six core courses:

• MDS 546 Methods of Exploratory Data Analysis
• MDS 523 Data Warehousing
• MDS 534 Introduction to Predictive Modeling
• MDS 560 Advanced Enterprise Analytics
• MDS 561 Data Governance and Project Management
• MDS 575 Generative and Applied AI

Students then complete four elective courses chosen from the MDSA program or other Elmhurst University master’s program in consultation with the MDSA program director. Sample MDSA electives include:

• MDS 535 Programming Environments for Modern Data
• MDS 564 Advanced Machine Learning Applications
• MDS 572 Time Series Forecasting
• MDS 576 Data Science Capstone

Sample Course Sequence

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