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Thread: Career change into (computer?) science at 27..?

  1. #1 Career change into (computer?) science at 27..? 
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    Hey, nice to meet you all!
    I'm currently 27 and work in the entertainment/media industry, which I've very much lost my passion for (and also find employment unstable). I've found over the last few years I've developed a surface interest in the sciences (I was always very good at these in school, just chose to follow a creative path instead). I particularly find myself gravitating towards the subjects of technology, AI, robotics, neuroscience, human-machine relations etc.. I am particularly interested in the developments in the relationships between humans and technology, and we seem to be in an exciting time to be working in these fields. So my questions are:

    What particular avenues of study (if any) and future career paths should I look into?

    Is 27 too late to be starting, given my complete lack of practical experience in these fields?

    Whilst I was once good at maths, I am very very out of practise, and also have no experience computer programming. I'm not really interested having to work all day with advanced mathematics or computer coding. Is this realistically going to be a problem?

    Thanks so much for any help at all. If you reply would you mind please stating your level of experience so I know where you're coming from.
    Regards


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  3. #2  
    Forum Radioactive Isotope MagiMaster's Avatar
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    If you have (or can handle) a mathematical mindset, then learning programming should be no huge obstacle. If you want to be a computer scientist of any sort, you will have to spend time coding though. All of the sub-fields you mentioned (and all of the ones you implied) require you to write your own programs to do various things and that can often take several days to several months (or more in some cases). (I can probably give you more details about a specific sub-field if you want.)

    Any university education in computer science will begin with various programming classes and the first few will be mostly concrete, teaching you the basics of one specific language. From there, things get more and more abstract as you learn about algorithms and then models of computation and so on.

    It's never too late to learn though.


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  4. #3  
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    Thanks Magi, which subfields are the least maths and code intense?
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    Quote Originally Posted by MagiMaster View Post
    All of the sub-fields you mentioned (and all of the ones you implied) require you to write your own programs to do various things and that can often take several days to several months (or more in some cases). (I can probably give you more details about a specific sub-field if you want.)
    Thanks magi, which subfields are the least maths/code intense?
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  6. #5  
    ▼▼ dn ʎɐʍ sıɥʇ ▼▼ RedPanda's Avatar
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    As an additional point: there are many free/open source programming languages available these days, so you should be able to find something suitable to practise on at home - once you have figured out exactly which direction you want your career to go.
    SayBigWords.com/say/3FC

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  7. #6  
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    Quote Originally Posted by TinSoldier5000 View Post
    Thanks Magi, which subfields are the least maths and code intense?
    Out of the fields you mentioned (there are too many for me to think through everything), human-computer interface research might be the least code intensive. You still need to write code for interface designs you're studying, but those can be smaller, example interfaces. If you're doing that kind of research though, you're going to need a lot of statistics to analyze the results. (That wouldn't be an every day thing, but it would be fairly intensive.) Human-computer interface design would be less math but more code as you'd be expected to build bigger, more complete interfaces more regularly.

    AI is very code (and often math) intensive. Robotics requires a moderate amount of code, but a lot of that code is very math intensive.

    Neuroscience isn't a computer science field, but I think you'd need some statistics to work in nearly any field of research except theoretical computer science or pure math. Any job in practical computer science would require a lot of coding.

    On the other hand, out side of computer science, you might be more interested in the various engineering disciplines. Computer engineering or electrical engineering don't involve much programming and might involve less intense math (though I'm not as familiar with either, so I can't be too sure). A computer engineer designs and builds new computer components, while electrical engineers handle more general electrical systems (again though, I can't give many details).
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    Hey, if you're doing it for the money, I would advise extreme caution. Its a cultish world, with a lot of discrimation based on age, and personality type. Its really not diverse in terms of types of people, and there is no garantee at all that CS degree will get you hired.

    One good reason to go into though is if you have brick and mortar experience in some other industry, and you know exactly what technical solutions that industry needs, where a normal computer nerd doesn't, so you alone can deliver.

    Another good reason to go into is if its your passion. As far as your question about maths and programming, the essential thing is intellectual rigor - the ability to think in those logical terms. Both math and programming develop that trait, and if you have that trait programming will be no problem. Without it, your ideas will be loosy goosy. There are a vast amount of people with loosy goosy ideas, and no $80,000 a year software engineers want to hear what they have to say, because its only rigorously defined ideas that can be translated into real technology. But if you are passionate about stuff like human computer interaction, developing that rigor is a small price to pay to see your dreams come to life.
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  9. #8  
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    Yeah, I was actually 27 when I decided that I wanted more excitement than that provided by accountancy and took the step into software. It lasted 20 years then I was struggling to keep up. During that time I got to like a lot of people. Like any journey you have to take the initial step. The only real way to learn is to find applications and use the software tools (which is what computer languages are) to solve those problems. You don't need to be great at mathematics but that certainly helps. The guys I knew who had maths degrees did seem to be that bit better. Those with computer science degrees didn't seem to be any better than those without. I encountered some with only minimal quals who were very good.
    If you can break into the field at all you have overcome the biggest barrier.
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  10. #9  
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    Utilise your transferable skills.....

    Though ICT is a very broad field...so you see where skills you've learnt beforehand can help you in your new career.
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    For a beginner in programming, I find Lua very easy to use. It is a prototype language, like Newtonscript or its inspiration, Self. Basically, to create a prototype-based system you create an object (let's say a fruit) with specific traits. A fruit object would have a color, a taste, and a shape. If you wanted to create a banana, you would make a method or function to duplicate the fruit prototype and set its properties to that of a banana. So the color would be yellow (when ripe), it would taste... well, like a banana, and be shaped like a crescent.

    Sorry for the bad explanation, but I find Lua is very enjoyable. While I have limited experience with Python, I have heard it is also a very versatile and useful language that seems to be somewhat similar to Lua.
    import antigravity

    Neurology is somewhat useful in the AI field; generally, Hebbian learning is good to learn about.

    I think AI is a very fun and innovative field that is making lots of progress in recent times.
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  12. #11  
    Forum Radioactive Isotope MagiMaster's Avatar
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    Python sort-of forces you to use good coding practices, which could be useful to a beginner. I'd recommend it.
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    It will be a problem if you want to work with complex (3D) graphics.
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  14. #13  
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    Yeah, I can't say I'd recommend Python for 3D, but then again, that's not really a task for a beginner anyway.
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  15. #14  
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    Quote Originally Posted by MagiMaster View Post
    Yeah, I can't say I'd recommend Python for 3D, but then again, that's not really a task for a beginner anyway.
    I was actually aiming that at the question as to whether or not he would need advanced maths .
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  16. #15  
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    Oh yeah. 3D does need a lot of math, but I didn't get the impression he was looking at any disciplines that involved much in the way of graphics.
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  17. #16  
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    Quote Originally Posted by TinSoldier5000 View Post
    Hey, nice to meet you all!
    I'm currently 27 and work in the entertainment/media industry, which I've very much lost my passion for (and also find employment unstable). I've found over the last few years I've developed a surface interest in the sciences (I was always very good at these in school, just chose to follow a creative path instead). I particularly find myself gravitating towards the subjects of technology, AI, robotics, neuroscience, human-machine relations etc.. I am particularly interested in the developments in the relationships between humans and technology, and we seem to be in an exciting time to be working in these fields. So my questions are:

    What particular avenues of study (if any) and future career paths should I look into?

    Is 27 too late to be starting, given my complete lack of practical experience in these fields?

    Whilst I was once good at maths, I am very very out of practise, and also have no experience computer programming. I'm not really interested having to work all day with advanced mathematics or computer coding. Is this realistically going to be a problem?

    Thanks so much for any help at all. If you reply would you mind please stating your level of experience so I know where you're coming from.
    Regards
    hey what you you wrote is exactly what I am interested in. Technology is growing faster and faster and it keeps expanding. I am more interested in the brain computer interferences (BCI) part because thing is that we don't have a very good understanding of the human brain so we still don't know what we can possible be able to pull of once we do find a better understanding of the brain. Right now we can control things using our neurons collected from something called an EEG (I don't know the exact process). Honestly this field got me interested from an anime called sword art online where people literally went to Virtual game through something called a nerve gear. Their whole consiouceness was in a game where they were virtually there while there bodies were on "sleep mode" until they logged off, thus creating a full augmented virtual reality game. After watching the show I started researching is that even possible and even though we barely have anything that matches what that does, we still are improving on what we can do with our brains and computer altogether. For example we can control a flying helicopter by just using our brain as a control (when you are plugged into a device that reads ur brain signals). Heck there were these two scientists/engineers who experimented with BCI and TMS where one scientist thought of something and with that brain signal created from a thought traveled to a server and back to the other guy where it controlled his finger which made him click a key allowing to fire this tRget in a game ( just type in BCI and TMS in google to find it out). anyways, a field that I found most similar was computational neuroscience (google it) which is an interdisciplinary field of study that coveres the topic fairly decently.

    Also, if anyone knows any other fields that matches with brain to machine interference please let me know since I'm currently 15 and am looking for a good career path to follow, thanks.
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  18. #17  
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    Also computational neuroscience is an interdisciplinary science that links the diverse fields of neuroscience, cognitive science, and psychology with electrical engineering, computer science, mathematics, and physics. (Wikipedia for more info)
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