Masters Concentration in Data Science: Pre-Application and Plan of Study

This form serves as the pre-application for the Computer Science Masters Concentration in Data Science. You must be enrolled as a UMass Amherst Computer Science Masters student before submitting this application. See http://www.umass.edu/gradschool/admissions/ for admission information.

Please indicate the program options that you are most interested in below. Your selections are non-binding and will be used for planning purposes only. Submission of this form does not guarantee you seats in any particular class. For full information on Concentration requirements, see https://www.cics.umass.edu/content/data-science. Questions about this program should be directed to askds@cs.umass.edu. 

Student Info
First and Last
Date of expected Graduation. e.g 5/11/17 or 2/1/19
Data Science Core Courses
Theory for Data Science Core Requirement
Systems for Data Science Core Requirement
Data Analysis Core Requirement
Students are required to take four data science core courses, one each in theory, systems, and data analysis, and one in any area. Please indicate the courses you plan to take below.
Data Science Elective Options
Data Science Elective Requirement - Internal
Data Science Elective Requirement - External
Indicate which of the following ares external to Computer Science you would be interested in taking Data Science electives in.
Students are required to take two data science elective courses. Courses are available through computer science as well as other departments. Please indicate the computer science courses and external departments you are interested in below.
Probability and Statistics
Probability and Statistics Requirement
Students are required to take one course in probability and statistics. Please indicate the course that you are most interested in among the options below.
Other Program Options
Masters Project
Optional Numerical Computing Course
Students are required to take three free electives (9 credits). Alternatively, students can complete a Masters Project (6 credits) and one free elective. Students are required to find a project advisor and the number of available positions may be very limited. Finally, the concentration includes one optional course COMPSCI 590N: Introduction to Numerical Computing with Python (1 credit) that is intended to provide background in numerical computing and Python programming needed for the data analysis core courses. Students that have no background in Python should consider taking this course, and will then complete a total of 31 credits. Please indicate your interest in these options below.
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