:bar_chart: Path to a free self-taught education in Data Science!
Hi! I love what you've put together here. Just a quick question on philosophy:
From what I understand, there's a level of formality to jumping in and doing this (i.e. tracking progress with webapp)
The guide states: "Should I take all courses? Yes! The intention is to conclude all the courses listed here!"
What's the view on jumping in where it seems appropriate?
In other words, people may be coming from a wide range of backgrounds such that some of the courses may not be a good investment of time (e.g. perhaps parts of the calc, probability, linalg, intro CS prereqs)
Not to get worked up about the details or anything, but just curious on the extent to which taking part in this is a formal process vs. a loose structure open to interpretation. :+1:
Hi @rreusser Welcome to Data Science channel
The intention is to cover as much prereq as possible without assuming anything about the learner's background
Also, to provide "Brush up" opportunity for people already comfortable, but definitely you can/should start at the appropriate level you feel
Hey! I will be starting the data-science path soon :smile:
A lot if not most of the content in the Data Science Nanodegree is already covered in the courses recommended by OSS, I dont know if it should then be recommended as a Specialisation for after youve finished all the MOOCs, as it doesnt really add anything new
I agree @JoshuaRowe11_twitter , its suggested not recommended though
hey, are you guys taking one course at a time?
Hi @arch1212 , it depends on how much time you devote... if you are working full time or have to attend school/college, then don't start more than 2 courses at a time ( doing 1 at a time is better)
else you can bump up the number , but try not to do more than 3 at once
Thanks @royshouvik I have just finished the Course on Git and GitHub. I am devoting my full time to this. But I have found that I am more productive if I concentrate on only one course at a time rather than taking a couple more. I tend to lose track and eventually fall behind.
Hey, Can anyone recommend projects for Statistics with R?
Hey @royshouvik . i have just started with data science course. Anything I should keep in mind while going through the course
@gmunish007 Can't think of anything specific.. Feel free to ask questions if something is not clear
Hello, is there any provision for the publication of the curriculum in data science?
Sorry, I found the course (or curriculum as I said earlier).
Hey everyone :smile:
Just want to ask, is there any textbook required to follow this path?
@wsr13990 the courses should be self sufficient, there are lot of great textbooks available on the internet if you are interested
@royshouvik We now have a new way to track our progress in the OSSU-CS curriculum. Maybe it would be helpful to do something like this for the DS course as well. In this section you can understand how it will be done now :smile:
@ericdouglas sweet! Standing on the shoulder of "Trello" giant ;) I will get it going for the DS curriculum as well
@royshouvik yeah, totally! You know:
"Simplicity is the ultimate sophistication."
Leonardo da Vinci
Has anyone completed all the courses as given? If so, how long did take you complete it?
Also how does this course compare with the data science master course
Hey guys, I just wanted to say a big thank you to everyone involved! Specially @royshouvik for starting this. :+1: I've been following the course for the past month + a few weeks, I finished the Linear Algebra section and I'm now working my way through Calculus, I was told these stuff in school and university, but I was never actually taught, now I'm actually learning the concepts in and out.
Good luck :+1: @mdibaiee
How long does it take to Complete all these courses on average ? Like 1000 hours or what can anyone here give me any idea about this so I plan my Studies accordingly 😐😐