(36 credits)
Program Description
Data analysts use business data from sources ranging from online dating, health care, transportation, industry, nuclear science, and many more to generate insights about populations and processes. Data analysis can be used to enhance productivity and increase profits, target medicines and treatments, optimize resource utilization, fight climate change, improve food production, and much more.
Students will learn to understand and apply the foundational concepts and methodologies that constitute data analytics from basic statistics to data visualization to machine learning for descriptive and predictive purposes. This program prepares students to work across diverse industries and organizations.
Learning Outcomes
(effective Fall I 2025; Summer II 2025 term uses catalog year 2024-2025 Program Learning Outcomes)
Upon completion of this program, students will be able to:
- Design relational databases using best practice principles;
- Construct data using data science functions, select programming languages, and associated data science libraries;
- Interpret selected datasets using a variety of statistical tools;
- Execute data mining operations on a variety of datasets;
- Create data visualization presentations using selected datasets.
Residency-Based Hybrid Delivery
The program follows a 3 term per academic year structure, with mandatory 3-day residencies during each term. Students must attend all residencies to continue enrollment in the program.
In the period before and after the residencies, students will complete their course work online. Instructors will maintain regular ‘virtual’ office hours and will be available to assist students as required throughout the term.
Course Map
Please visit the course map by term for this program here: Data Science and Analytics, MS (Executive Hybrid) Course Map
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