​MS in Data Analytics & Statistics

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.

  • The MSDAS degree requires 30 units, which may include optionally 6 units for thesis.
  • Required courses (15 units) for the MS degree include:
ESE 520Probability and Stochastic Processes3
or Math 493Probability
ESE 524Detection and Estimation Theory3
Math 494Mathematical Statistics3
CSE 514AData Mining3
or CSE 517AMachine Learning
or CSE 530SDatabase Management Systems
ESE 415Optimization3
or ESE 516Optimization in Function Space
or ESE 518Optimization Methods in Control
Total Units15

  • The remaining courses in the program may be selected from senior- or graduate-level courses in ESE or elsewhere in the university. Courses must be in technical subjects relevant to statistics, optimization, computation, or applications of data analysis and require the department's approval.
  • Program tracks in Statistics; Optimization and Decision Theory; Computing are available.
  • A maximum of 6 credits may be transferred from another institution and applied toward the Master of Science degree. Regardless of subject or level, all transfer courses are treated as electives and do not count toward the requirement of 15 credit hours of graduate-level electrical engineering courses.
  • The degree program must be consistent with the residency and other applicable requirements of Washington University and the School of Engineering & Applied Science.
  • Students must have a cumulative grade point average of at least 3.2 out of a possible 4.0 over all courses applied toward the degree.