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    ionakathryn
    @ionakathryn
    im trying to decide whether or not to go developer or data science route - what about you?
    Srikant Mahapatra
    @SassySamurai

    @ionakathryn: Focus is DIFFICULT to attain; no shit! I suggest you start a meditation practice. Meditation has been shown in various research studies to improve attention, focus and overall mental well-being. You can start with Headspace: https://www.headspace.com. They have a free track called "Take 10" which comprises of ten guided meditations, one per day. This has even been recommended by Tim Ferriss. It also seems that you might be having problems with motivation. If that's the case, I suggest you stop counting on motivation and start counting on discipline instead. Read this: http://www.wisdomination.com/screw-motivation-what-you-need-is-discipline/

    Regarding the career choice between a software developer or data scientist, if you're looking for advice, I don't have any because I haven't started my career yet! I was initially traveling on the data science route but then I chose to fulfil my childhood dream of becoming a game developer, so I have now taken a detour to the development side. I believe in Cal Newport's philosophy that "skills trump passion in the quest for work you love." Basically, "be so good they can't ignore you."

    ionakathryn
    @ionakathryn
    ahha thanks @SassySamurai are you following the bioinformatics path? i dont tend to struggle with focus when learning specific things, i mean the bigger picture, like what to learn e.g java, c , python etc i get excited about all the possibilties of what to learn haha :joy: i am trying to meditate for 5mins/day. i know this isnt much at all, and some days i dont even manage it but its better than nothing! :P
    Srikant Mahapatra
    @SassySamurai
    @ionakathryn, if you're going the data science route, then let me tell you this: you have to be really good at the math behind data science in order to do anything meaningful in this field. Just knowing the various algorithms and how to apply them won't suffice; you have to understand why they work. Not much math is required for software development, though, unless you're planning to work in a math-intensive field such as computer graphics, game development, simulations, etc.
    ionakathryn
    @ionakathryn
    what about working in a medical field with programming e.g genetic research , does this come under data science and needing to learn lots of math?
    ionakathryn
    @ionakathryn
    and also what about machine learning/ AI / Business intelligence? Does the same apply?
    Srikant Mahapatra
    @SassySamurai
    @ionakathryn: Machine learning and AI are heavy on math. So any field that makes use of these require you to be proficient in math. I don't have anything to say about bioinformatics, genetic research, etc. except that they require proficiency in biology obviously. I don't think they're as math-intensive as core ML and AI. There are a lot of good bioinformatics courses on the Web. You might wanna check 'em out.
    mattialife
    @mattialife
    Hello
    everybody
    Mahdi Dibaiee
    @mdibaiee
    @mattialife Hi
    ionakathryn
    @ionakathryn
    THanks for the info @SassySamurai :)
    djaballah
    @djaballah
    what are the mathématique prerequesties to learn machine learning
    Anwesh Nayak
    @anweshknayak
    @djaballah probability, linear algebra and calculus would do if you want to begin. rest you can pick up while you studying
    Srikant Mahapatra
    @SassySamurai
    Probability's child, statistics, is also important.
    Anwesh Nayak
    @anweshknayak
    anyone has benefitted yet from this course ? Please share your experience if anyone has
    Felipe Peressim
    @feperessim
    I love data science. And I want to follow this path into it. The problem is that I am very bad at probability.
    Last semester I studied a lot to pass the class pf probability and statistics
    Also studies a lot of combinatories. Which I don't remember so much now.
    What is your advice to me?
    Shouvik Roy
    @royshouvik
    @feperessim I would say just keep practicing and you will get better eventually...
    Isak Falk
    @IsakFalk
    @feperessim Coming from a mathematical background, I would say that knowing the definitions inside out helps. Humans are notoriously bad at intuitively using probability and interpreting statistics, that is why this formality with probability and statistical theory comes from, it enables us to make less mistakes by making sure that we don't do leaps unconsciously.
    And practice makes perfect as with everything.
    janaemy
    @janaemyfr_twitter
    Hi, Someone can share his succes storie :smile:
    Mahdi Dibaiee
    @mdibaiee
    Oh, now that you've asked for it :D
    I started taking this path around 6 months ago I think, and now I'm on Probability and Statistics, it helped me deepen my knowledge in Machine Learning and now I'm an intern in a company (gradually becoming an NLP Engineer). I'm sure I wouldn't be as efficient in understanding Machine Learning concepts was it not for the Mathematics behind it. And the courses in this path are probably the best out there, you can hardly find anything better :D
    Shouvik Roy
    @royshouvik
    :+1:
    Guys also check out http://course.fast.ai/
    Mahdi Dibaiee
    @mdibaiee
    I can never thank the guys behind this project enough, specially @royshouvik :D :pray:
    Shouvik Roy
    @royshouvik
    Thank you for your kind words @mdibaiee but it's you who deserves the credit for your success! Wish you many more :sparkles:
    janaemy
    @janaemyfr_twitter
    Waw @mdibaiee that's beautiful dude ! I'm so glad to hear this. I'm trying to motivate peoples to learn by itself. And I'm currently writing an article about. Can you share you're success story with us by writing some words. It's for the french community :smile:
    here is my mail, janaemy@protonmail.com
    Mahdi Dibaiee
    @mdibaiee
    @janaemyfr_twitter I see! sure thing, I'll shoot you an email
    janaemy
    @janaemyfr_twitter
    Great thank you :+1: I waiting for it :)
    Shouvik Roy
    @royshouvik
    @mdibaiee hows your studies coming along?
    Jun Xiong
    @suredream
    Hi Guy, may I ask who even use beakerX before? Or any other better place to ask such question?
    Mahdi Dibaiee
    @mdibaiee
    @royshouvik Hey Shouvik, thanks for asking! Still on Probability and Statistics: Inference from Berkeley :bar_chart:, I'm going through my finals right now so I'm a little slower on the progress, but will reinforce right after my exams :fist: :D
    Mahdi Dibaiee
    @mdibaiee
    :joy: :joy:
    karishma3397
    @karishma3397
    hello
    i wanna learn ml
    from where should i start
    anithp
    @anithp
    @karishma3397 i would suggest andrew ng's ml.
    Claire Kirby
    @depeche-toad
    Hello, everyone. To those doing the Data Science path, are you also doing the Springboard Data Science Career like OSSU recommends, or just doing the free OSSU data science path?
    Shouvik Roy
    @royshouvik
    @depeche-toad AFAIK, almost no one is doing the Springboard course (probably because of the cost it involves)
    Smaily
    @Smaily1
    Hello world !
    Mahdi Dibaiee
    @mdibaiee
    @Smaily1 Hello! :smile:
    jacoblindberg
    @jacoblindberg
    In https://github.com/open-source-society/data-science it says Introduction to Data Science is 8 weeks with 10-12 hours/week but when I click on the link I get to https://www.coursera.org/specializations/data-science which is actually four courses! Is the link wrong?
    Mahdi Dibaiee
    @mdibaiee
    @royshouvik Hey Shouvik! I recently got to Convex Optimization, but I found the material in need of more advanced topics than the ones in the path, the Linear Algebra is more advanced and it requires skills of writing and reading mathematical proofs. Do you think we could add Books to the path? I couldn't find MOOCs for these topics, but I'm currently reading "How to Prove it" by Daniel J.Velleman and then I'm going to read "Linear Algebra Done Right" by Sheldon Axler
    Shouvik Roy
    @royshouvik
    Hey @mdibaiee It's possible that the curriculum is not perfect, and some courses require more prereq than already covered because
    1. I didn't complete all of the courses my self :) In fact I completed very few
    2. I knew less about Data Science at that time than today
    The curriculum grew out of my own need of a decent path to follow for learning Data Science/Machine Learning which I couldn't find at that time...So I would say, feel free to discuss and suggest improvements wherever possible
    I am planning to do some major overhauls to the curriculum, make it more lean and targeted ...but my hands are more than full right now :(