(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
Upon completion of this program, students will be able to:
- Collect, clean, and transform data from a variety of sources into useful data to drive business decisions;
- Design and query databases to organize large amounts of data;
- Interpret data using a variety of statistical tools;
- Execute real-time analytics using stored and live datasets to quickly respond to customer needs;
- Communicate insights effectively using data visualization and reporting tools appropriate for diverse audiences.
- Perform data science and analytic functions using the Python programming language and the associated Python Data Science libraries.
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
