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Does it really matter from which college you graduated

I have nearly 2 decades experience in data management, but no degree. I've started taking classes at a community college but am trying to determine where to finish a BS/BA. The catch, it has to be 100% online degree program from a regionally accredited university in the US.

Given my age/stage in my career and the variance in cost and prestige of the available programs, I ask you this:

Does it really matter from which college you graduated? 

Which is more important, the college name or degree? 

Is a college nationally ranked at 50, better than one ranked 130?  

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At your level of experience, the school doesn't matter. If you are earning the degree, so you can be promoted or will satisfy requirements for jobs, to which you plan to apply, just go with the "path of least resistance". If you are looking to add to your background (e.g., learn about machine learning methods), then look for the program that provides what you want, but again, the actual school will have little impact, for someone with 20 yrs of experience. 

Thanks for the reply, Bob. I agree with your assessment, however, in the back of my mind, I keep having a feeling I might regret going for the quickest/cheapest degree. For example, two schools I'm considering from opposite ends of the spectrum are Penn State and Southern New Hampshire University. I think I'll learn something useful either way, so I'm not too concerned with the education aspect. You get out what you put in, and all that.

Again, I appreciate the response.

Bob Vanderheyden said:

At your level of experience, the school doesn't matter. If you are earning the degree, so you can be promoted or will satisfy requirements for jobs, to which you plan to apply, just go with the "path of least resistance". If you are looking to add to your background (e.g., learn about machine learning methods), then look for the program that provides what you want, but again, the actual school will have little impact, for someone with 20 yrs of experience. 

IMHO two forces are at work here, one in your favor and one perhaps not so.  First, there is a significant shortage of well trained and experienced data scientists (you didn't say but I assume you're studying data science).  That shortage works in your favor.  Employers also statistically favor a formal course of education at an accredited school to self guided programs like MOOCs.

If it is data science you are pursuing at the undergraduate level, make sure the degree is specific to data science and machine learning, not more generally to computer science.  Masters degrees are preferred but you can offset that with a solid portfolio.  Make use of any project time to try to build as many 'documented' projects as possible to illustrate your competence.  That's always my first question to newbies - what types of problems have you built models for and what specific tools (algorithms, languages, techniques) can you prove to me that you've mastered.  Just saying you took the course is not enough.  As you do these projects think about how you will briefly describe them in an interview to present and document your experience in the most positive way.

As to the credentials of the schools, if your choice is between the 50th and 130th ranked school (who did the ranking?) I'd say that's pretty much a wash unless one has particular name recognition.  Paragraph 2 is more important.

There are a handful of elite employers and we all know who they are that can command graduates from the top schools with the top experience.  But the penetration of predictive analytics in US business in estimated these days to be about 40% and in a large company, that probably means several clusters of data scientists in different parts of those organizations.  There's plenty of room in the middle.

Perhaps a more important question since you are apparently over 40 is 1.) where do you want to live - and by extension does one of those colleges give you a geographic advantage, and 2.) less pleasant is that you may get to do more interesting work but may initially have to take a step back in pay.  Also unpleasant is that there does appear to be some ageism in hiring which you may be able to offset with a strong portfolio of documented data science projects.  Volunteering or interning to get to participate in those projects may be something to think about.

Good luck.

Good points - thanks, William.

William Vorhies said:

IMHO two forces are at work here, one in your favor and one perhaps not so.  First, there is a significant shortage of well trained and experienced data scientists (you didn't say but I assume you're studying data science).  That shortage works in your favor.  Employers also statistically favor a formal course of education at an accredited school to self guided programs like MOOCs.

If it is data science you are pursuing at the undergraduate level, make sure the degree is specific to data science and machine learning, not more generally to computer science.  Masters degrees are preferred but you can offset that with a solid portfolio.  Make use of any project time to try to build as many 'documented' projects as possible to illustrate your competence.  That's always my first question to newbies - what types of problems have you built models for and what specific tools (algorithms, languages, techniques) can you prove to me that you've mastered.  Just saying you took the course is not enough.  As you do these projects think about how you will briefly describe them in an interview to present and document your experience in the most positive way.

As to the credentials of the schools, if your choice is between the 50th and 130th ranked school (who did the ranking?) I'd say that's pretty much a wash unless one has particular name recognition.  Paragraph 2 is more important.

There are a handful of elite employers and we all know who they are that can command graduates from the top schools with the top experience.  But the penetration of predictive analytics in US business in estimated these days to be about 40% and in a large company, that probably means several clusters of data scientists in different parts of those organizations.  There's plenty of room in the middle.

Perhaps a more important question since you are apparently over 40 is 1.) where do you want to live - and by extension does one of those colleges give you a geographic advantage, and 2.) less pleasant is that you may get to do more interesting work but may initially have to take a step back in pay.  Also unpleasant is that there does appear to be some ageism in hiring which you may be able to offset with a strong portfolio of documented data science projects.  Volunteering or interning to get to participate in those projects may be something to think about.

Good luck.

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