丁香园AV

Students can apply directly into the Data Science program from high school or as a transfer student. Instructions for how to apply can be found on the 丁香园AVs site. For any admissions-related questions, please contact the Faculty of Science Recruitier, Claire Wilson (science_recruiter@sfu.ca).  

Students of Fraser International College can now transfer directly into the Data Science program at 丁香园AV. 

For a prospective Data Science student who is unable to transfer directly into the program, please refer to the question below for current 丁香园AV students. 

Students already accepted to, or studying at, 丁香园AV must consult with the Data Science Advisor about admission to the program. There are three criteria for admission:

1. Student must have a minimum of 6 required Data Science courses completed at 丁香园AV.

2. Minimum 2.7 DATA GPA (the DATA GPA is the GPA across all courses required for the Data Science major that were completed at 丁香园AV). You can use the GPA calculator to determine your DATA GPA.

3. Minimum B- in at lease one required CMPT course, one STAT course, one MATH/MACM course, and one BUS course.

Note: If you are currently outside of the Faculty of Science, you will first need to transfer into the faculty before declaring your major (please see the requirements for an internal transfer at the top of this page).

If you are interested in applying to complete Data Science as a second undergraduate degree, it is recommended that you first consult with the Data Science Advisor. Please also see the "Second Degree Students" section below for further details about completing Data Science as a second degree.   

For those who completed their original degree at 丁香园AV:

You can simply apply for reactivation by completing the form on this page. Choose "Science" as the faculty when completing the form. If approved by the faculty, you will initially be labelled a "non-degree-seeking student". Once you have been deemed eligible to do so by the Data Science Advisor, you can then declare your major in Data Science and become a second degree student. Eligibility is determined on a case-by-case basis.

For those who completed their original degree elsewhere:

Follow the instructions on this page under the section labelled "University graduate (degree holder)". You will need to initially apply as a "non-degree student" in the Faculty of Science. When you are admitted, and once you have been deemed eligible to do so by the Data Science Advisor, you can then declare your major in Data Science and become a second degree student. Eligibility is determined on a case-by-case basis. 

It depends on your 鈥渞equirement term鈥�. A requirement term is the semester in which you were admitted to a program. You can find your requirement term on the first page of your advising transcript under "Req. Term". It is a four-digit number that starts with '1' and ends with 1/4/7. The middle two numbers indicate the year. The last number indicates the semester (1=Spring, 4=Summer, 7=Fall). So, for example, 1237 is the semester code for Fall 2023.

To find the requirements for your requirement term, go to the Academic Calendar listing for the Data Science major (or Data Science honours, if applicable). In the URL, change the year and semester to match your requirement term. For your reference, the most recent changes to program requirements for the Data Science major/honours occurred in: 1177 (Fall 2017), 1194 (Summer 2019), 1214 (Summer 2021, 1217 (Fall 2021), and 1237 (Fall 2023). 

Consult with the Data Science Advisor about this (or any other case in which you have completed a course that you believe is equalivent to a required course). In certain cases, course substitutions can be made. CMPT 130 and 135 is a common subsitute for CMPT 120 and 125.

MATH 157 and MATH 158 are acceptable (but not recommended) for the Data Science program requirements. However, there are two required CMPT courses that have MATH 150/151 as a prerequisite: CMPT 276 and CMPT 307. Students with MATH 157 wishing to enroll in CMPT 276/307 should consult with an Applied Science Advisor (asadvise@sfu.ca) in advance of their enrollment date.

The Data Science program is quite structured, with limited room for electives beyond Breadth requirements. Currently, the Data Science major program requirements involve 55-57 lower division units and 43-44 upper division units, which adds up to 98-101 total units.

Of the required coursework, students will meet the university's Writing requirements (both lower and upper division), the Quantitative requirements, the Breadth-Science requirements, and 3 out of 6 units of the Breadth-Social Science requirements. This leaves 3 B-Soc units and 6 B-Hum remaining to meet the WQB requirements. Including these 9 breadth units, Data Science students have 10-13 extra required units that they can take as electives, to meet the required 120 overall units, including 44 upper division units.  

There are certain key courses that it is important to take early on in the degree. Notably these include: MATH 150/151 and MACM 101; CMPT 120, CMPT 125, CMPT 127, and CMPT 225; an introductory Statistics course (STAT 201/STAT 203/STAT 205/STAT 270); and DATA 180. Please take a look at the lists of Suggested Course Enrollments below.

DATA 180 is a one-unit seminar class only offered in Fall semesters. The class takes place once a week for two hours (usually on Tuesday evenings from 6:30-8:30pm). Each week, a different speaker comes in to discuss their area of specialty. Guest speakers can include data scientists (and people working in related roles), past students, and career/co-op advisors.

There is a continuance requirement of a 2.7 cGPA among required courses in the Data Science program (you can use the DATA GPA calculator to determine your Data Science GPA). Each semester your DATA GPA will be checked. If it drops below 2.7, you will first be issued a warning. If your DATA GPA drops again the next semester, you will be discontinued from the program. Should your program GPA rise to at least a 2.70, you could be re-admitted. Please consult with the Data Science Advisor to discuss your situation.

Yes, students can add a minor/major in any subject area to their major in Data Science (provided that they meet the requirements to be approved into the minor/major).

For a Data Science student wishing to complete a minor or second major in Statistics, Computing Science, Mathematics, or Business, please refer to this clause in the :

Students wishing to complete a second major or a minor in addition to a Data Science (DATA) major must satisfy all DATA requirements. At least 34 upper division units must be allocated exclusively to the DATA major.

This includes at least nine units from each of the lists under the sub-headings Business Administration, Computing Science, and Statistics. Units used to satisfy DATA upper division requirements beyond these 34 can be applied simultaneously to the other major, minor or honours.

So, for example, if a Data Science student were to pursue a minor in Computing Science, they would still need to take all of the required UD CMPT courses (i.e. CMPT 307, CMPT 310, CMPT 353, and CMPT 354). However, only 9 of these 12 UD units would have to be applied to the Data Science upper division units. The other 3 UD units could then be applied to the Computing Science minor. In other words, beyond CMPT 307, 310, 353, and 354, a Data Science student would need 4 extra UD CMPT courses (i.e. 12 UD CMPT units) to complete a Computing Science minor.  

Yes, there are three different options for a Data Science honours program: 1. Statistics concentration; 2. Mathematics concentration; and 3. Open concentration. Please refer to the . In addition to following the program requirements, a student is required to complete at least 60 total UD units to complete the honours program. 

Please see the "丁香园AV" section above for details on how to apply as a second degree student.

Second degree students need to complete all required upper division courses, and any lower division courses that are prerequisites for upper division required courses for which the student does not have equivalent credit for from their first degree. Calculus I and II are required for all 丁香园AV Science degrees. Please see the Course Prerequisites and Course Availability list to see what courses are prerequisites for required upper division courses. Send the transcript from your first degree to the relevant department advisors to determine what lower division courses you have from your first degree, and to have those prerequisite waivers added to your 丁香园AV record.  Forward the responses to the Data Science Advisor together with your full name and 丁香园AV student number.  

A student with an academic background unrelated to Data Science would likely need to take all lower division courses with the exception of certain lower division BUS courses (BUS 200, 251, and 272) and MATH 208W. STAT 240 and CMPT 276 would also not be required for such a student, but are recommended.

If you believe that you have equivalent credit for a course that is a prerequisite for a class you would like to take at 丁香园AV, you will need to email your transcript to the Advisor who oversees that subject area. For example, if you took Calculus 1 in your first degree, and you would like to enroll in MACM 101, you will need to email your transcript to Applied Science Advising (asadvise@sfu.ca), requesting permission to enroll in MACM 101. It is recommended that you do this in advance of your enrollment date.  See above request to send your transcript to relevant department advisors for course evaluation.

Depending on what course load you are comfortable with, as well as what you have credit for from your first degree, a second degree in Data Science could be completed in as few as 4 semesters.

For example: