Data AnalyticsMaster of Data Analytics (MDA)
Program ContactBethany Heinrichs (firstname.lastname@example.org)
Professional Program Coordinator, Master of Data Analytics
The Master of Data Analytics (MDA) is designed to produce technical professionals ready to pursue an analytics-focused career within the public and private sectors.
The program, building on students’ core competencies in computer science and statistics, equips them with a set of highly sought-after, interdisciplinary technical data analytics skills. Students are also provided with the opportunity to customize their learning experience through the selection of a specialty field. The program culminates with an experiential learning opportunity consisting where students will get practical, hands-on experience using the analytics skills in a workplace environment.
- 3 Terms (1 year)
- Full-time study
Potential applicants are strongly advised to consult the MDA program’s website for full details about admission requirements that are summarized below. To do so please click Data Analytics on the above right sidebar of this webpage.
Overview (consult the MDA program website for full details):
- Completion of an undergraduate degree with a minimum 75% average
- Prerequisite courses for all specialty fields:
- Two half courses of Calculus
- One half course of Linear Algebra
- One half course of Probability (Calculus-based)
- One half course of Statistics (Calculus-based)
- Two half courses in Computer Programming
- One upper year mathematically mature half course
- Additional prerequisite courses for the Artificial Intelligence specialty field:
- One half course in Data Structures and Algorithms
- One half course in Software Tools and Systems Programming OR Software Design
- One half course in Logic for Computer Science
- An average mark of at least 75% in prerequisite courses is required for an application to be viewed as competitive. Applications with marks of at least 75% in each of the required prerequisite courses will be viewed as more competitive.
- The above coursework must have been taken for credit at the undergraduate or graduate level at an accredited university. Study through online certificate programs will not be considered.
- Applicants will be required to provide documentation about their prerequisite coursework by uploading a course outline/syllabus for each course requirement as listed on the program website. The Admissions Committee will assess this documentation to determine if the content of such courses meets the requirements for admission. Examples of prerequisite courses from Western are listed on the program’s website so that potential applicants can gauge whether their prerequisite coursework meets such standards.
English Language Proficiency
Applicants whose first language is not English must furnish evidence of their proficiency in the use of the English language. Note that the English Language Proficiency requirements for the MDA program admission exceed the standard university requirement for graduate level studies because students in the MDA Program are called upon to exercise their communication skills frequently through class discussions, written assignments, group work and oral presentations. For full details on the MDA program’s English Language Proficiency requirements, please click Data Analytics on the above right sidebar of this webpage.
- October 15 – Application system opens for the following September.
- November 15 - Students who apply by this deadline will receive consideration for the first round of offers.
- February 15 – Students who apply by this deadline will receive consideration for second round offers.
- February 15 - Final deadline for all international applications.
- June 15 - Final deadline for all domestic/permanent resident applications.
Please note: Applicants may be required to complete a technical skills assessment and interview as a part of the admissions process.
Program entry will occur in the Fall term.
- Term 1: 2.5 FCE including 4 core and 1 specialty field courses Career Development Seminar Series (bi-weekly)
- Term 2: 2.5 FCE including 3 core and 2 specialty field courses Career Development Seminar Series (bi-weekly)
- Term 3: Experiential Learning Opportunity (12 week co-op/internship/Major Research Project)
Fields of Research
- Artificial Intelligence
- Finance, Banking, and Insurance