Evaluation for Graduate Study

Following are our assumptions for this automatic evaluation form:

  • English: Applicant must fall in one of the following:

Have English as their first language.
Have a four year degree from U.S. or Canada.
None of the above but with TOEFL.

  • Grade: Applicant must fall in one of the following:

Percentage (90, 85, 80, 77, 73, 70, 67, 63, 60, 57, 53, 50, 0)
Letter grade ( A+, A, A-, B+, B, B-, C+, C, C-, D+, D, D-, F) Guelph graduate only
GPA of scale (4.3, 4.0, 3.7, 3.3, 3.0, 2.7, 2.3, 2.0, 1.7, 1.3, 1.0, 0.7, 0)

Applicants who do not satisfy the above assumptions are advised not to use this automatic evaluation.

Notes: Items with *are mandatory

First Name*

Middle Initial

Last Name*


Mailing Address

Street Address*

City*

Province

(For Canada/ U.S. only)

Postal Code

Country*

Home Telephone*


(country)


(area code)


(number)

Email Address*


Personal Information

Date of Birth*

(Example:31-Jan-1980)

Gender

Female Male

Status in Canada*

Country of Birth*


Admission Test Scores

For International Students: A TOEFL score is required if English is not your first language and/or you are not a graduate of a four-year degree program from Canada or U.S.


Is English your first language?
Yes No

Do you have 4-year university degree from Canada or U.S. or are you completing such degree within 6 month ?
Yes No

TOEFL

Date Taken

(Example: Apr 2002)

Test Format

Paper-Based
Computer-Based

Score Received


GRE (optional)

Date Taken

(Example: Apr 2002)

Verbal score

Quantitative score

Analytical

Subject Test

 

Date Taken

(Example: Apr 2002)

Score

Required Courses

Applicants must have at least 75% average for 11 of the following courses (or equivalent). For detail description of these courses, please visit: CIS Courses Description, MATH/STAT Courses Description

For each CIS/MATH course, please select your grade (choose one).
Note: Letter grade system is used by Guelph graduate only

·  An object-oriented programming course such as CIS*1650 or CIS*2430

Percentage

Letter

Alpha

·  An advanced programming course such as CIS*2650

Percentage

Letter

Alpha

·  CIS*2420: Data Structure

Percentage

Letter

Alpha

·  CIS*3110: Operating System

Percentage

Letter

Alpha

·  CIS*3200: Software Engineering

Percentage

Letter

Alpha

·  CIS*3490: Algorithm Analysis

Percentage

Letter

Alpha

·  CIS*3530: Database

Percentage

Letter

Alpha

·  CIS*4050: Computer Architecture

Percentage

Letter

Alpha

·  A computer networks course such as CIS*3210 or CIS*4200

Percentage

Letter

Alpha

·  CIS*4600: Computation Theory

Percentage

Letter 

Alpha

·  CIS*4750: Artificial Intelligence

Percentage

Letter 

Alpha

·  CIS*4760: Image Processing

Percentage

Letter 

Alpha

·  CIS*4800: Computer Graphics

Percentage

Letter 

Alpha

·  Three university level MATH/STAT courses

Percentage

Letter

Alpha


Education

Please list Institutions where bachelor's or higher degrees were awarded or expected to be awarded below in the last institution first order.

Name of School

Location (Country)

Grade (choose one)

Percentage

Letter

Alpha

Major

If not found, enter

Degree

Date Received

(month/year)


Name of School

Location (Country)

Major

If not found, enter

Degree

Date Received

(month/year)


Name of School

Location (Country)

Major

If not found, enter

Degree

Date Received

(month/year)

Research Interest

Please select your research interest from the following list:

Data and Knowledge Management (DKM): Students working in this field will engage in research on topics such as bioinformatics and biocomputing, data mining and machine learning, geographic information systems, image analysis, information retrieaval, relational and deductive database systems, uncertain inference and decision support systems.

Distributed Computing (DC): Students working in this field will engage in research on topics such as distributed database systems, distributed systems and mobile agents, embedded systems and multi-agent systems..

Applied Modeling (AM): Students working in this field will engage in research on topics such as environmental modeling, optimization algorithms, performance analysis, and simulation.

Natural Computation (NC): Students working in this field will engage in research on topics such as genetic algorithms and neural networks.


 

I hereby certify that all information given here are correct and best to my knowledge.