Data Science & Analytics Master’s Degree
The DSA is designed with an in-depth, technically-rigorous core curriculum followed by domain-specialized emphasis area courses. Advanced Big Data and Analytics tools and techniques are used throughout the program coursework. Courses are delivered as 8-week online modules. Additionally, students spend one week each spring on campus with faculty during an executive session.
Data Science as a Collaborative Lifecycle
We teach data science as a collaborative lifecycle, where data and processes have provenance from the raw data stage through to the resulting business intelligence products. A data lifecycle starting with data curation, exploratory data analysis, statistical and machine learning modeling and refinements, and decision product production is used to tell the story of the data.
Two key philosophies drive this:
Students will work closely with faculty mentors, gain experience through solving real-word Big Data issues, explore concepts targeted to their emphasis and more.
The capstone project teams up students with faculty & members of industry for hands-on experience with large data sets and the latest technology and techniques.
Required Credits: (34 Hours)
- 19 Credit hours for Data Science Core Curriculum
- 9 Credit Hours for Emphasis Area courses
- 3 Credit Hours of Case Study
- 3 Credit Hours Capstone
that I have learned is how to clean up data…how to figure out what is most important and how to tell that story with great visualization.” Renee Henderson
The diverse student backgrounds enable some lively discussions and numerous perspectives based on prior experiences and the diverse industry background. We strive to enhance student learning of technology in cooperative, team oriented settings.
Students are routinely (weekly) tasked to perform cooperative communication with fellow students to help them develop their communication and collaboration skills around the technical coursework and subject matter.