Reacting to an increasing popularity for the field, and seeing an increase in the job prospects for data science students, UT Austin is introducing a new major this fall. This major is Statistics and Data Science, and will offer a BS through the College of Natural Sciences.
In this article, we’ll break down what the new major offers, and who will benefit from it. We’ll give some advice on how to apply to this major specifically through UT Austin’s “Why Major” essay, and discuss how this major can impact your application strategy for UT Austin. Let’s get started!
What the Data Science Major Entails
Currently, this major is only open to freshman applicants; while transfer students may be able to apply for it in the future, they are not accepting transfer applications in the 2022-23 admissions cycle.
The major requires 120 course hours to graduate, which encompass the following areas:
- 7 courses in the major (22 credit hours)
- 5 foundation courses in math and computer science (17 credit hours)
- 4 courses to fulfill the breadth requirement (courses must be in a single field of study, and be taken outside the department) (12 credit hours)
- Two courses of departmental electives (6 credit hours)
- 10 courses of free electives (30 credit hours)
- 11 courses for the core curriculum (33 credits)
While this curriculum requires a fair amount of computer science and programming, no knowledge is required in these areas before entering the major. (Though we do think admissions will prioritize applicants with a background in CS).
The goal of the breadth requirement is to give you a chance to explore a subject area you would like to tie data science to. For instance, if you wish to pursue pharmacological applications, you would take courses in biochemistry, whereas if you wanted a career as an archivist, you would take courses in the humanities or social sciences.
Overall, the major provides students with a solid grounding in both math and computer science, along with baseline programming knowledge, and enough of a foundation in another field to make these skills immediately applicable in the jobs market. While some data science positions desire more advanced degrees, most are more than willing to hire students with only a bachelor’s, and the growth of the field means that there are plenty of positions available for graduates.
How to Apply to the Major
As with any other major at UT Austin, you can select the major when applying online, either via the Common App or ApplyTexas. There are no specific additional requirements for the major, but your application should be positioned to support your preparation for and interest in data science.
For the best chance of acceptance into the major, you should focus on two things. The first is your extracurricular activities, and the second is your “Why Major” essay, which allows you to explain directly to admissions officers why you want to study this particular subject. We’ll cover each of these in turn.
Extracurriculars for Data Science
The extracurriculars that position you well for data science are the same as those which will position you well to study math or computer science. Participating in math-based competitions (and performing well), knowing programming languages and coding for fun, and involving yourself with computer-centric organizations all demonstrate a passion for subjects central to the major.
While there are few activities which specifically involve data science open to high school students, there are many options which require you to learn and utilize the skills which the major requires. Many of these activities can also position you well for a CS major; we’ll explore how this can help you in the strategy section below.
The “Why Data Science” Essay
We’ve discussed how to write “Why Major” essays before, but now we’re going to dive a little into how to compose one of these essays to talk about data science (and this particular program) specifically.
Your essay should spend the bulk of its space discussing why you are interested in data science, and any prior experience you have had with the field. The extracurriculars we discussed above are a rich source for this, as they provide solid evidence to support any points you make.
You can either focus on one activity you participated in in depth, or peruse a multitude of different engagements. Due to the limited length of the essay (300 words), we generally recommend exploring a single topic in more depth, as this allows for a more thorough examination of your accomplishments and motivations. Your activities list can then show the breadth of your accomplishments in the field.
If you have not participated in any extracurriculars related to the field, the essay is slightly more difficult to approach. We recommend beginning with any classes you may have taken. If you deeply enjoyed a computer science class (or two, or three) at your high school, that could easily turn you on to data science.
We recommend not focusing on future earning potential or the desires of your parents in this essay. Both of these are seen as more shallow reasons for pursuing a major, and are not looked upon favorably by admissions officers. That said, if one or both of your parents work in data science, and this is how you were first introduced to the field, that can form the beginnings of a good essay. You should, however, still focus on how you explored and interacted with the field after this initial exposure however.
Finally, you should briefly discuss why you want to study data science at UT Austin specifically. This should not be the main point of your essay, but devoting a few sentences to this at the end can have a big impact. Be very specific, though this is a new program, it already has some aspects which set it apart (like the breadth requirement). The more specific you are about why this program will support your goals in data science, the more admissions officers will be able to picture you succeeding at UT Austin.
Data Science Application Strategy
The announcement of this major is great news for students who wish to study computer science at UT Austin. CS is by far the most competitive major at the school (more so even than business or engineering), and many talented students are rejected. This major allows another approach to study a similar topic, including CS courses, and to enter a similar field.
If you are a competitive applicant, but are uncertain about your odds for CS, we recommend considering an application to the Data Science major. While it is likely to be popular, its relative newness will make it less competitive than the already well-established computer science program.
Data science can also be used as a second choice major if you are applying to CS. As we discussed in a previous article, second choice majors are rarely relevant, but this is a case where it may have more of an impact.
Overall we recommend this major to students who want to study computer science at UT Austin’s renowned facilities, but who are worried about their chances of admission. While the curriculum is not exactly the same as a CS degree, it does impart many of the same skills, and will allow you to pursue many of the same opportunities, while being far more attainable.
Of course, this is the first year this major has existed, and the first class of applicants who are applying to it. While we stand by our predictions, we cannot see the future. We will update this article with more pertinent advice on your actual chances of admission once those are more firmly established.
Final Thoughts
Computers have ushered in a bold new age of technology, and careers dealing with them are increasingly prevalent. Data scientists work to handle, refine, and interpret the mountains of information generated by computerized systems, and turn it into results which are easily accessible and usable by a broader audience. UT Austin’s new program is set up to help students access this growing field, and the numerous new career opportunities it affords.
While this is a new program, UT Austin has long been the best public university in the state of Texas, and has seen its applications grow and acceptance rate decline in recent years. For a complete guide to UT Austin’s admission process, check out our free ebook. If you want help with your data science application, or want to hear how we can help you maximize your chances of acceptance into UT Austin, schedule a free consultation today. We’re experts in the admissions process, and our students are 2.4x as likely to get into UT Austin than the average.
