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).
Students complete two project-based courses, providing an environment for integrating lessons learned from the program’s multifaceted 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 Introduction to Business Intelligence, Data Mining, and Predictive Modeling
- MDS 560 Business Intelligence for Enterprise Value
- MDS 535 Programming Environments for Modern Data
- MDS 556 Analytical Methods for Machine Learning
- MDS 564 Advanced Machine Learning Applications
- MDS 576 Data Science Capstone
- Students will complete two additional elective courses from the MDSA program or another approved Elmhurst University graduate program.
Program Format
- A part-time program that can be completed in two years
- Fully online, with classes that are flexible to accommodate the schedules of professionals with work and family commitments
- Students complete coursework through eight-week sessions, one course at a time
- This program starts in the Fall and Spring terms
Sample Course Sequence
Fall A
- MDS 546 Quantitative Methods
Fall B
- MDS 523 Data Warehousing
Spring A
- MDS 534 Introduction to Business Intelligence, Data Mining, and Predictive Modeling
Spring B
- MDS 560 Business Intelligence for Enterprise Value
Summer
- Elective
Fall A
- MDS 535 Programming Environments for Modern Data
Fall B
- MDS 556 Analytical Methods for Machine Learning
Spring A
- MDS 564 Advanced Machine Learning Applications
Spring B
- Elective
Summer
- MDS 576 Data Science Capstone
Elmhurst University reserves the right to modify courses, schedules and program format without advance notice to students.