The MS in Data Analytics and Statistics (MSDAS) is an academic master's degree designed for students interested in learning statistical techniques necessary to make informed decisions based on data analysis. It is aimed at harnessing the ever increasing amounts of data now available to gain new insights. Data analysts utilize machine learning and statistical tools to approach these problems. This interdisciplinary field is at the intersection of systems science, computer science and engineering, and mathematics, all of which are required for the goal of developing the skills to gather, process, analyze, model and optimize the resulting solutions.
This program has coursework broken up into four primary focus areas: mathematical probability and statistics, computational tools and machine learning, optimization methods, and applications. These courses are split between requirements in these four areas, as well as electives chosen from these areas.
Students have gotten internships or upon graduation have gone to work in industry as researchers, analysts and software engineers at companies such as; Amazon, Bayer, Bosch, Citigroup, Deloitte Consulting LLP, The Federal Reserve, and GE.
2 ESE 529 allowed as a substitution of ESE 524 for students entering the program prior to Fall 2020.
Requests for exceptions to this policy may be submitted to the department chair with the approval of the academic advisor of the student.