MS in Applied Computing in Data Science atUniversity of Toronto Department of Computer Science

No specific cutoff mentioned

No specific cutoff mentioned

• Completed or be the process of completing an appropriate undergraduate degree for the concentration they are applying to.

• An appropriate bachelor’s degree from a recognized university in a related area such as statistics, computer science, mathematics, or any discipline where there is a significant quantitative component.

• The program will consider admitting candidates without an undergraduate degree in computer science, statistics, or a related field, but who show a demonstrated aptitude to be an excellent data scientist. Applicants should be able to demonstrate a potential to conduct and communicate applied research at the intersection of computer science, statistics, and a domain area.

• Background academic preparation to be successful in graduate-level computer science and statistics courses typically, though not always, includes intermediate or advanced undergraduate courses in the following topics: 

  • Algorithms and Complexity, Database Systems, or Operating Systems. 

  • Statistical Theory/Mathematical Statistics, Probability Theory, or Regression Analysis.

• A standing equivalent to at least B+ (U of T 77-79%) in their final year (i.e., two terms) of study (the equivalent of 5 full credits, or 10 half credits).

• Work experience (including co-op placements or internships) is preferred, but not required.

• Research experience (including summer research assistantships or internships) is preferred, but not required

Yes

• Three year bachelor's degree is also acceptable

Marks - 93/120

• Minimum of 22 on both the Writing and Speaking sections

Marks - 7/9

•  with at least 6.5 for each component.

Not mentioned