Admissions

The Master of Data Analytics (MDA) program is technically rigorous. To be considered for admission to the MDA program applicants must meet all of the minimum requirements listed below. Study through certificate programs or online institutions such as Coursera will not be considered. The following coursework must have been taken for credit at the undergraduate or graduate level at an accredited university.

Please note:  The assessment of a potential applicant’s chances of admission will not be provided in advance by email.  Potential applicants should carefully compare their background to the admission requirements as listed below and ensure that they meet all of these requirements prior to applying.  Applications that do not meet these minimum requirements will not be considered.

Review the Application Timeline page for a complete list of required documents and the timeline of the MDA Admissions process.

MDA Admission Requirements: All Specialty Fields

Undergraduate Degree

Prerequisite Courses

Please Note: One half-course (0.5) equals three hours of class time per week, or a combination of class and laboratory work of four hours per week, for the duration of one four-month academic term (e.g. September through December). A full-course (1.0) equals the same number of hours per week for the duration of two academic terms (e.g. September through April). Courses offered in a two-month condensed format – such as some summer term courses - will consist of six to eight hours of class/laboratory hours per week.

This list of prerequisite courses represents the minimum requirement to be eligible for consideration. Note that applications can be strengthened by achieving grades of at least 75% in additional coursework in Statistics, Probability, Computer Science, and Mathematics. The majority of such courses should be non-introductory.

English Language Proficiency (ELP)

Please see our English Language Proficiency Page for complete details about this requirement.

Additional Requirements for Artificial Intelligence (AI) Specialty Field

Students interested in the AI speciality field need to have completed these additional courses (or equivalent) in order to meet admission requirements. A familiarity with Linux is assumed.

All AI prerequisite courses must be a 2nd-year course or higher and achieve an academic score of 75% or above.