I recently got accepted into the data science program at UCSD, I have heard that getting degree in data science puts you at a huge disadvantage when applying for job placements or even applying for graduate school as compared to getting a degree in computer science.
Is it really that big of a difference between getting the two degrees at UCSD ?
Data science is very hot right now. It’s a combination of math, CS and statistics. There are plenty of opportunities for students with that background.
I agree with @bouders . Unless you want to be a software engineer specifically, Data Science is a great field, a very applied sort of math.
What do you want to do, or do you know yet?
I don’t know what discipline I want to do in computer science. I haven’t had that kind of exposure to the field yet.
I’m going to try and answer this from a UC-Berkeley perspective, which may or may not be the same elsewhere. I’m somewhat a good person to answer this question because I am in the DS field and my kid is a dual CS/DS wannabe major at Berkeley.
DS is a very hot field right now, it just officially became a major at UCB this academic year. In a couple of years, it undoubtedly will be the most declared major, I predict. From a difficulty standpoint, if you look at the requirements needed to get through CS and DS, CS is way way more difficult (may change in the future). Pretty much every required lower-division CS class and every upper-division CS class is challenging, high workload, and difficult to almost-impossible difficult. I honestly can say that the first required DS class at Berkeley is easy, and the second DS class at Berkeley is easy to medium. (I hope no one at Berkeley figures out who I am). The DS curriculum has a lot of flexibility, so if someone wanted to skate by with a bunch of easier classes, they possibly could. To me though that would be a waste of an education, but I’m sure some people will do that. A lot of the curriculum is interspersed with CS classes though, so DS can be challenging as well. As far as CS goes, it’s virtually impossible to skate by, you absolutely earn your CS degree at Berkeley.
So having said that, those $150-200K starting salaries you see being offered aren’t going to DS majors. They’re going to the top CS majors, and probably only from certain elite schools (UCSD possibly being one of them). However, there is a big demand for data scientists and data subject matter experts, so plenty of jobs exists though. They won’t pay as much, I’m pretty sure of that.
Data science is hot, but it is new, So the quality and content of the new educational programs vary. I’m not familiar with the program at UCSD. A CS program with machine learning, statistics, and big data courses might be more of a sure thing. Maybe major in CS and minor in DS?
Are you accepted to DS but not to CS, or you haven’t heard from CS? What’s the decision here, UCSD DS or some other school totally?
I got into UCSD DS but I got into CS at other schools but they are not as good
While this is true for CS jobs, it’s not so for DS jobs.
As a data point, a young person I know who graduated with a DS/Stat degree got a terrific job doing CS with a 6 month crash course not only paid for by the company but with the almost full salary while doing that. You can change course if you want to.
You can possibly do more CS courses in your DS program (as extra electives?) if you want that focus. Plenty of software engineers teach themselves to code, or add languages, and/or pick up skills in other ways.
But if you are totally set on CS, it may be best to go where you can major in it.
Besides “not as good”, are there cost differences between the schools? Location? Fit?
Have you looked at the different major requirements?
https://datascience.ucsd.edu/academics/undergraduate/major-requirements/
Data Science degrees can vary considerably. There are data science or data analytics degrees out of business school that have very little computer science. Others have a fairly high computer science content (up to around 50% of computer science credits taken by actual CS majors, possibly more with choice of electives taken).
I think the latter is very marketable today (the former may or may not be).
One exception might be a DS degree with electives in deep learning/machine learning. But the prerequisites for these courses would include calculus, linear algebra, probability and statistics and algorithms, so it would still be a rigorous program.
Tufts (which is much smaller than UCSD) offers a Data Science degree from the Computer Science department. They have a guide to the Data Science major on their web site that addresses the question of choosing between the degrees.
https://engineering.tufts.edu/cs/bachelor-science-data-science
UCSD provides this information on the various computing majors- the tricky part is that at UCSD, it appears that both CS and data science are capped majors, so it may be hard to switch between them.
http://computingpaths.ucsd.edu/
CS is a very broad field and has many subfields (or “tracks” as they’re called in some colleges). I personally consider DS one of its tracks, even though DS has become an independent major at many colleges. CS major requirements typically include a broad set of cores (from low level system architecture to abstract theory of computation, etc.) to reflect the breadth of the field. DS major typically foregoes some of that breadth, and focuses more on its specialization.
^This. I always thought of DS as a branch of CS. I know that the position my D took with her new company that they have a one year rotation of three “disciplines”…one being software development, one being data science/analytics and one being AI/ML…so both employer and employee are able to distinguish the best fit going forward. My D is a double major, Math and CS, and so is in a good place to do well in all three tracks.
Interesting thread and commentary. It will certainly evolve as universities build programs tailored to CS/CE/DS. UVA is opening a data science center enabled by a large private donation: https://news.virginia.edu/content/uva-plans-new-school-data-science-120-million-gift-largest-university-history
I would say that Data Science is the application of computers to analyze very large data sets in a particular domain of interest.
So it is an interdisciplinary, applied, major that can either be viewed as an evolution/automation of the discipline of Data Analytics required by “Big Data”, or as an application of the discipline of Computer Science (featuring the relatively new sub discipline of AI/ML) to “Big Data”.
As a result, the major can either be offered by a Math department or a CS department with the balance between Analytics and CS often reflecting the sponsoring department.