Are Graduate Data Science Programs A Marketing Tactic?

The question may be worded weird but I was watching a YouTube video of a gentleman deciding between a MS in Statistics at UCLA or UC Berkeley or a MS in Data Science at Harvard University. In his video, he gave a warning that Data Science programs are typically courses compiled from statistics, mathematics, computer science, and business departments rather than a program with its own unique, and new, curriculum. This got me wondering what others thought on this as I had never given it too much thought.

video (he has phenomenal reasoning for choosing UCLA over UC Berkeley and Harvard FYI):

 

The problem with a specific degree is extremely hard to mauver in different career fields. Instead of going for a Master in Cybersecurity, for Master in Computer Science or a Master in Information Technology. Master in Management, should be Master Business Administration.... Data Science should fall under Computer Science, Information Technology, or Statistics.

 

Yes, data science is a hot career right now so data science programs are in vogue - they're a good moneymaker for the school.

There was a time when the same was true of operations research, cybersecurity (as TEKMAN) notes, and other fields where it appears the 'money is'. Data science degrees do cannibalize their courses from other disciplines because data science is itself a marriage of statistics, computer science and an x-factor of domain knowledge.

Someone with an MS in Stats probably lacks the computer programming knowledge (in many universities) to immediately become a data scientist while someone with an MS in Computer Science probably lacks the statistics knowledge they need, at least on the basis of a regular degree plan and not one made with this career in mind.

Whether data science degrees make sense in the long-term is hard to say. There's already a turf war over whether whether data science as a field should contain machine learning and artificial intelligence, or whether those are separate fields. So you see people saying "Data science is dead, long live the Machine Learning Engineer" and other things like that.

There are only a few PhD programs in Data Science right now (my program is taught by people with doctorates in Experimental Psychology, Statistics and Computer Science and no one with a PhD in DS) , but most data scientists at FAANG companies have PhDs, in fields like Computer Science. This is another point towards data science not really being its own discipline, or at least not well-developed enough to merit its own PhD programs.

 

I agree that Data Science is a very hot field. My programming Professor at Duke did his MS in Statistics and works for the largest healthcare company in North Carolina as a Data Scientist. In today’s day and age, statisticians use coding day in and day out for their positions.

I personally see no issue with interdisciplinary programs. In fact, I find it useful to have a broad skill set and then fine tuning from there. I found it interesting that he said to avoid them though. Why apply if you do not believe it is a legitimate degree program to pursue? Ya know?

 

Good point. This might be controversy for the sake of controversy (and monetized YouTube views), or it might be a way to justify his decision. Maybe he didn't even get into Harvard and he's just claiming that he did? (I didn't watch the video so maybe he provides proof.)

Over on Reddit there's one person named u/HarvardHopeful2020 who does nothing but bash Quantic because after they were rejected they decided it was a totally fake worthless MBA, which gives me similar thoughts.

 

I love those folks. Lol All gung-ho until they get rejected and then it becomes a sham.

 

Okay, this made me laugh: https://www.eastern.edu/sites/default/files/inline-files/job_437.pdf

My school's looking for a Professor of Data Science but they don't want the professor to have a doctorate in data science. Instead they say "Candidates should possess a graduate degree (a Ph.D. is preferred) in Statistics, Computer Science or Applied Mathematics".

 

I would assume by opening it up to Statistics, Computer Science and Applied Math, they will get far more applicants than had they said they prefer Data Science. All 3 of those fields are insanely quantitative and coding is used extensively.

 

You're right, those would all be excellent fields to hire from. But it's funny that they don't even mention DS in a TT Professorship for Data Science.

 

Statistics was one of the hardest classes in college for me, followed by math, I was good at it but it was at the cost of my sleep.
Later I had another applied informatics class that used statistics, math, and computing heavily but it was fascinating because it was well balanced between the theoretic and applied data science.
These type of classes were not in the curriculum for MS in Statistics.