Core coursework is designed for students to develop a foundation in statistical analysis and cultivate technical skills in programming, data mining, machine learning, database management, and data and network security. Students also develop techniques to effectively visualize and then communicate results to stakeholders.
Statistical Foundations for Data Science
Doing Data Science
Applied Statistics: Inference and Modeling
File Organization & Database Management
Data and Network Security
Visualization of Information
Quantifying the World
Students are required to take two elective courses to be completed in their last two terms. The elective coursework allows students to customize more in-depth competencies in a range of data science-related disciplines.
Students may choose a specialization as their elective coursework. Two specializations are offered – Machine Learning or Business Analytics. The specializations are custom curriculum options for students who desire a tailored approach to learning and a thorough understanding of subject matter specific to their academic and career goals. Specializations are available for all students but are not required. Students who do not pursue a specialization have the option to select the electives that best fit their overall goals.
Natural Language Processing
Time Series Analysis with R
To better prepare students for the academic rigor of the Master of Science in Data Science program, there are two self-paced bridge courses available — a refresher course in statistics as well as a course in programming using Python and R. These self-paced courses are designed to help you review statistical and programming knowledge before classes begin.