Grad School Choices: Comp Sci at Concordia or Math at UoT?

In summary, the person has been offered admissions to Concordia University with funding for a master's in computer science and possibly admissions to University of Toronto for a master's in math with no funding. They are wondering which is the better choice and the response is that it depends on the amount of debt they are willing to take on. They chose the smaller school because it offered support and they are planning to pursue a PhD after. They suggest contacting people in each department to learn about the opportunities and considering factors such as thesis project, courses, and potential supervisors rather than just the school's reputation. They also suggest considering personal interests in math or computer science when making the decision.
  • #1
Dragonfall
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I've been offered admissions to Concordia University (not very well known) in comp sci with a little funding, and (maybe) admissions to University of Toronto (a lot more renowned) in math with no funding. Both are a master's (which is a pre-requisite for a PhD in almost all Canadian universities).

What's the better choice?
 
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  • #2
She sells sea shells by the sea shore.
 
  • #3
It depends on how much debt you want. I was in the same position you are in last spring and chose to go the the smaller school (where I got my BS) because they offered me support while others did not. I did this because I'm going on to get my PhD and didn't want to start off 4-5 years of school with debt. Are they both doing research in the area that you want to work in?
 
  • #4
You'll probably get a better answer by contacting people in each department - proffs, grad students, academic advisors, etc. and learning about the opportunities each school has to offer. Consider what you would be doing for your thesis project, what courses are available, and the personalities of potential supervisors. All of these factors are far more important than how well known a school's name is.
 
  • #5
Maybe the question you should be asking yourself is...which do i like more? math? or computer science? then you might have your answer.
 

1. What are the program requirements for a graduate degree in Computer Science at Concordia?

The program requirements for a graduate degree in Computer Science at Concordia include a bachelor's degree in a related field, a minimum GPA of 3.0, letters of recommendation, and a statement of purpose. Some programs may also require standardized test scores and relevant work experience.

2. What is the curriculum like for a graduate degree in Mathematics at the University of Toronto?

The curriculum for a graduate degree in Mathematics at the University of Toronto will vary depending on the specific program and specialization. However, it typically includes advanced coursework in topics such as algebra, analysis, geometry, and statistics, as well as opportunities for research and thesis work.

3. How long does it take to complete a graduate degree in either Computer Science at Concordia or Mathematics at the University of Toronto?

The length of time it takes to complete a graduate degree in either Computer Science at Concordia or Mathematics at the University of Toronto will vary depending on the program and the student's course load. On average, a master's degree can take 1-2 years to complete, while a PhD can take 4-6 years.

4. What are the research opportunities like at Concordia and the University of Toronto?

Both Concordia and the University of Toronto offer a variety of research opportunities for graduate students in Computer Science and Mathematics. These may include working with faculty on ongoing research projects, conducting independent research, or participating in research groups and seminars.

5. How do the job prospects differ between a graduate degree in Computer Science from Concordia and a graduate degree in Mathematics from the University of Toronto?

The job prospects for graduates with a degree in Computer Science from Concordia and a degree in Mathematics from the University of Toronto may differ slightly, as they are in different fields. However, both fields are in high demand and offer a wide range of job opportunities in industries such as technology, finance, and research.

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