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

Completion of an undergraduate degree with a minimum 75% average

Applicants must possess a four-year degree from an accredited university with a minimum average of at least 75% in the last two years of full-time undergraduate study.

Admission into the MDA program is a competitive process. This means that students who meet the minimum requirements are not guaranteed admission into the program; the academic average required for entry into the program may be above 75% based on the applicant pool.

Regardless of discipline, prospective students must achieve 75% or better in all prerequisite coursework to be considered for the MDA program.

Fields of study that successful candidates come from include:

  • Computer Science
  • Statistics

Or other fields with significant quantitative coursework in mathematics, probability, statistics and computer programming, such as: 

  • Actuarial Science
  • Financial Modelling or Financial Mathematics
  • Applied Mathematics or Mathematics
  • Physics
  • Economics
  • Computer Software Engineering

Prerequisite Courses

Two half courses of Calculus

For example, completion of the following Western University courses (or equivalent):

Calculus 1500A
Calculus 1501B

One half course of Linear Algebra

For example, completion of the following Western University course (or equivalent):

Mathematics 1600

One half course of Probability (calculus-based)

For example, completion of the following Western University course (or equivalent)

Statistical Sciences 2857

*Please see the FAQ section for a description of what is meant by a calculus-based probability course

One half course of Statistics (calculus-based)

Completion of the following Western University course (or equivalent)

Statistical Sciences 2858

*Please see the FAQ section for a description of what is meant by a calculus-based Statistics course

One upper year mathematically mature half course

Completion of mathematics courses that are 2000 level or above (or equivalent) from the following list:

Mathematics Courses

Completion of statistical science courses that are 2000 level or above (or equivalent) from the following list:

Statistic Courses

Completing of mathematically intense computer science course such as one of the following Western University courses (or equivalent)

Computer Science 3340
Computer Science 4413
Computer Science 4424
Computer Science 4445
Computer Science 4487

Two half courses of Computer Programming

Completion of the following Western University courses (or equivalent)

Computer Science 1026
Computer Science 1027

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.

One half course in Data Structures and Algorithms

For example, completion of the following Western University course (or equivalent)

Computer Science 2210

One half course in Software Tools and Systems Programming OR Software Design

For example, completion of the following Western University courses (or equivalent)

Computer Science 2211, or
Computer Science 4471

One half course in Logic for Computer Science

Completion of the following Western University courses (or equivalent)

Computer Science 2209

*Completion of a degree in the following disciplines will satisfy this requirement:

  • Computer Engineering
  • Mechatronic Systems
  • Software Engineering