Demystifying the computer/data science CODO process

In recent semesters, an increasingly large number of students aim to CODO — Change of Degree Objective, essentially switching majors — into the Department of Computer Science to varying degrees of success. As someone who has successfully CODO’d into the Department of Computer Science to major in data science as well as being in contact with students that have attempted/are attempting to/have successfully CODO’d (both friends and students I have TA’d for), I have discussed the CODO process countless times. Misinformation has certainly been spread. In this post, I will detail the CODO requirements and give some commentary on how to increase one’s chances.

My information comes from two official sources: the College of Science’s Academic Advising’s CODO Requirements for 2019-2020 and the Department of Computer Science’s CODO Requirements.

[EDIT 2020 April 13]: I’d like to mention that outside of parts that make direct use of official sources, much of this blog post was written with some guess work. While I wrote this after having had successfully CODO’d into data science, I know more now than I knew then. Unfortunately, the things I have since learned and confirmed are not things I can make public, sorry.

Chances

[EDIT: SEPT24] Before getting into the requirements, I want to give the one thing I have hard data for: the actual probability of getting into CS:

As per this article by the Purdue Exponent:

	Fall 2018	Spring 2019	Summer 2019
Total CODO applications	34	95	40
Acceptance rate	59%	53%	47.5%

The hard requirements

“Calculus course” in the course requirements is a bit misleading, as there are certain calculus courses that are implicitly not considered (MA 16010, 16020) and non-calculus courses that are considered (MA 26500, 35100). From the College of Science’s Academic Advising’s CODO Requirements for 2019-2020:

Grade of B or higher in a Calculus course approved to meet degree requirements – MA 16500, MA 16100, MA 16600, MA 16200, MA 26100, and/or MA 27101. MA 26500 and/or MA 35100 can be considered.

CODO Requirements for 2019-2020:

These are hard requirements for a CODO to be sent in and reviewed. CODOs not meeting these requirements are automatically rejected.

The soft requirements — the highest consideration clause

In the Department of Computer Science’s CODO Requirements (interestingly not in the College of Science’s Academic Advising CODO Requirements), there’s an excerpt that gives a secondary set of soft requirements, that meeting these requirements will explicitly make the candidate more competitive.

Students wishing to receive highest consideration should earn an A- in CS 18000, B or higher in an approved Calculus course which will be used to meet degree requirements, and have a minimum 3.00 cumulative GPA.

CODO Requirements Effective Fall 2018 admits and forward

Owing to the fact that more and more high school students apply to major in computer science and more and more students attempt to CODO into the department, these requirements become less and less soft as competition increases. This is further cemented by conversations with students retaking CS18000 despite having a grade above the minimum B requirement but having a grade below the A- highest consideration requirement. Extraordinary circumstances aside, meeting the soft requirements are necessary for acceptance.

[EDIT 2021 March 23]: I don’t think this is true anymore (now, at least). I don’t know if this is a recent trend where students that don’t meet this set of requirement are more common, or if holistic review has become more forgiving.

The data science application

Students looking to major in data science must also fill out an additional application. This is in addition to the CODO process. This application consists of two parts:

• Constructing a miniature plan of study by naming the semester one plans to take the following classes:
  • CS 38003 – Python Programming
  • CS/STAT 24200 – Introduction to Data Science
  • STAT 35500 – Statistics for Data Science
  • CS 25100 – Data Structures and Algorithms
• A statement of purpose, explaining why the candidate wishes to major in data science.

The statement of purpose should be thorough but also succinct. A paragraph or two is sufficient.

Holistic review

Outside the weird possibility that reviewing CODO applications is done by calculating a composite score from the candidates GPA, calculus grade and CS18000 grade, staff in charge of reviewing CODOs will take a broad analysis of the candidate in other classes they have taken. Indeed, both pages say:

Due to high demand for the CS program and present enrollment in the program, all CODO approvals will be made on a SPACE AVAILABLE BASIS and will be determined through a holistic review of all applicants. 

CODO Requirements Effective Fall 2018 admits and forward

Further, data science CODOs involves a committee process.

The most straightforward way for a candidate’s CODO to be competitive is to take further classes in the computer science sequence. With the declaration of a CS minor (requiring a C minimum in CS18000), one can take CS18200, CS24000 and CS25100 in off-peak semesters (fall for CS 18200 and CS 24000, spring for CS 25100, summer for all). There are other more fringe options as well. Some options are:

• CS10100 — Digital Literacy. This is more of a flare class that doesn’t really teach you any programming.
• CS15900 — C Programming. This is for those that plan to CODO right away but are not able to take CS18000 in the spring. Be careful taking this class (I’ve written my thoughts about this in another post), it won’t prepare you for other CS classes. Do not take it after having taken CS18000.
• CS17700 — Programming with Multi-Media Objects. Like above, take this before CS18000 but not after. This is particularly helpful for those trying to CODO into data science, as it takes the place of CS38003—Python Programming.
• CS19300 — Tools. This class is required to be taken as a computer science/data science major.
• MA37500 — Introduction to Discrete Mathematics. This course takes the place of CS18200 and can be taken without declaring a CS minor. This is useful for students who want to CODO right away as they can take this class a semester before or the same semester as CS18000.

Computer science vs data science CODO odds

I’ve had conversations with numerous people (and read conversations online) that carry the sentiment that CODOing into data science is a safer choice than computer science. Do not do this.

The chances aren’t much better

It’s reasonable that fewer people try to CODO into data science per semester than computer science. It’s a newer program and more fringe program after all. However this is offset by the fact that the data science program is tiny. By a back of the envelope calculation, data science is at least two times smaller than computer science, and I wouldn’t be surprised if it’s smaller.

[EDIT SEPT24:] Here is a more thorough calculation: There are seven computer science advisors. There is only a single data science advisor and this person does not only advise data science students, but also math students. From here CS is at least seven times larger than data science.

Hell, the College of Science’s Academic Advising CODO Requirements page says that

Space availability in the program will be very limited.

Data Science Special Notes

and computer science doesn’t.

The curricula differ substantially

Majoring in data science does not give the same opportunities that majoring in computer science does. Data science is far narrower in scope; whereas the computer science program offers nine unique tracks, data science does not. Comparing curricula, data science is a more comprehensive version of the machine intelligence track, having more statistics courses. If your sole interest in majoring in computer science was to get involved in machine learning and artificial intelligence, data science has a better curriculum. If you had any other interests whatsoever, it’s not worth it. Data scientists are edged out by computer scientists for everything else all else equal.

It’s also worth noting that even if you do have interests in machine learning and/or artificial intelligence, you can still do multiple tracks in computer science should you have other interests as well. It’s only in the very specific case where that’s your sole interest should you choose data science.

Sample applications

I’m not a fan of looking at other people’s applications and using it to judge one’s own chances but I’m sure people will be looking for information anyways.

My CODO application

This is essentially my transcript after Spring. I’ve put important classes in bold.

Other CODO applications

Thanks to the r/Purdue Computer Science CODO Results Megathread, there are a few more public CODO application results. There’s not much variation here; all that had their CODO accepted met the highest consideration clause.

Conclusion

In this blog post, I walked you through the CODO process and gave you some commentary on which requirements matter (it turns out all of them do) and how to make your application more competitive. This post also discussed which major to pick and previous CODO results. If you have any questions, I recommend you contact an advisor, but I can also respond to the best of my ability. For those of you waiting on CODO results or looking to CODO in the future, I wish you good luck.