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I apologize if this is not the appropriate site or the appropriate type of question, but I didn't know where else to ask. If it is, please inform me to delete the question.

I took a year in college and wasn't ready and so did horribly. However, A couple of years later now I am definitely ready to go back. I've been self-studying mathematics and a bit of programming and plan on starting to study more in depth topics in computer science. My plan is to go to a community college for a year or two then transfer to Rutgers to get an M.A. in mathematics while self-studying computer science in particular machine learning and computer vision. My question is this. Is this at all practical. What are the chances of success? I don't want to put all my eggs in one basket and end up failing because of a questions that I could have asked now and have to end up working as a cashier at McDonalds for the rest of my life. If you can offer me any advice it would be greatly appreciated.

AlexHeuman
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  • That is entirely practical, but keep an eye on where the industry is going. Make sure you have practical experience in areas that employers are seeking. The current job market gives employers much leverage in hiring. Employers look for candidates that have very specific experience doing tasks that are on their radar. If you haven't already done this, setup a profile on https://www.linkedin.com/nhome/. Start networking now and watch for job postings that look like they overlap with your educational interests. Augment your studies to achieve competency with skills that are in demand. – user2718 Mar 02 '13 at 21:12
  • Thanks BZ that's great advice. It really eased my spirits, and I completely forgot about linkedin. – AlexHeuman Mar 02 '13 at 21:25
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    To add to what @BZ has said, make sure that there is at least some correlation between your passions, and between knowing a skill set that is practical. Do you feel passionately about Computer Vision? If so, go do it! The world is your oyster. Dont do it just because you can make money with it - make sure you like what you do, and money will generally always follow. ;-) – Spacey Mar 02 '13 at 21:47
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    @Mohammad, I really could care less about money. As long as I have enough to have some food to eat and a bed to sleep in I'm not in it to be rich. I just think that math and computer vision are the only things things that I feel passionate about. I just don't want to go down a career where the prospects of getting a job are extremely difficult with a math degree. – AlexHeuman Mar 02 '13 at 21:50
  • I've had to deal with job insecurity for years. I've been fortunate enough to keep myself employed, but having to wonder if your job is going to be shipped over seas or become obsolete is no fun. Life is a balance. Stay alert to what is going on in the real world and you'll do fine. – user2718 Mar 02 '13 at 22:09
  • Sounds like reasonable advice. I'm definitely going for it then. – AlexHeuman Mar 02 '13 at 22:28
  • @AlexHeuman Thats good then. Remember, balance. "Make sure you do something you love, and never have to work a day in your life" applies. I think you certainly cannot go wrong with Signal Processing, and/or Computer Vision. Certainly be strong in Applied Math, always with an eye on something that is applicable. If you have passion you are 90% there. Good luck! :-) – Spacey Mar 02 '13 at 22:49
  • Do you think I would still be acceptable to employers with a math degree and not a computer science degree though? – AlexHeuman Mar 03 '13 at 00:39
  • @AlexHeuman I am currently looking for my first job/internship and, from what I have learnt from HR and senior people, your motivation and potential are way more important than your knowledge. Everything can be learnt. And I think math is always a good background. – Serge Mar 03 '13 at 08:40
  • @AlexHeuman: I'd say in computer vision, a math degree is probably worth more than a computer science degree. Because teaching yourself the CS needed to write vision software is far easier than teaching yourself the required math. Applied math, machine learning, and some CS is really the perfect combination for computer vision. – Niki Estner Mar 03 '13 at 18:31
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    @Serge That's always something to keep in mind, and good luck with your search. – AlexHeuman Mar 03 '13 at 20:11
  • @nikie That was my thinking. I thought having a deeper understanding of math would allow me to have a finer understanding of the mathematical part behind it, while the CS part might be a bit easier to learn. Vielen Dank. – AlexHeuman Mar 03 '13 at 20:13

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