Western Michigan University, Master of Science in Data Science, 4 Semester(s)

This is an interdisciplinary master's program offered by the departments of Computer Science (CEAS) and Statistics (COAS). Half of the coursework for the degree consists of graduate courses in computer science while the other half consists of graduate courses in statistics. Graduates will be able to store and access data from a variety of sources, process Big Data architecture, apply analytic techniques and algorithms to large and complex data sets, apply data processing and visualization, work in collaborative teams, and communicate effectively. The capstone for the program is a master’s project course taken over two terms. In this course the student chooses a problem (topic) in Data Science on which to work under the supervision of a CS and/or STAT faculty member(s). At the end of the first term, the student will turn in a written proposal defining the problem, proposed solution(s), and a complete literature search. In the second term, the student will obtain a solution to the problem and present a written report defining the problem and his/her solution. Examples include: an ... Read more

This is an interdisciplinary master's program offered by the departments of Computer Science (CEAS) and Statistics (COAS). Half of the coursework for the degree consists of graduate courses in computer science while the other half consists of graduate courses in statistics. Graduates will be able to store and access data from a variety of sources, process Big Data architecture, apply analytic techniques and algorithms to large and complex data sets, apply data processing and visualization, work in collaborative teams, and communicate effectively. The capstone for the program is a master’s project course taken over two terms. In this course the student chooses a problem (topic) in Data Science on which to work under the supervision of a CS and/or STAT faculty member(s). At the end of the first term, the student will turn in a written proposal defining the problem, proposed solution(s), and a complete literature search. In the second term, the student will obtain a solution to the problem and present a written report defining the problem and his/her solution. Examples include: an unsolved problem involving data science at a local industry, an unsolved consulting problem involving data science drawn from a research problem at WMU, or an in depth study of a computationally intensive statistical method. Best projects, written in Sweave or Latex, will be submitted for publication in Data Science journals.

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