:bar_chart: Path to a free self-taught education in Data Science!
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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.
@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
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
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)
@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
I didn't complete all of the courses my self :) In fact I completed very few
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 :(