iNeuron - Full Stack Data Science Bootcamp

[AfroDR]

@Satoru Gojo , thanks a million for this upload.

 

[nollyesq]

Instead of asking for alternate links, try to find ways to download them by yourself. It's not that hard or expensive.

please how can i find it to download

 

[hellodear]

How do you guys download such big files? i tried to extract the files using google collab and was thinking of accessing this course from the drive itself but failed to do so. Can someone help on how did you download these files from google drive and how do you extract such huge chunk of data?

 

[cloudpilot]

How do you guys download such big files? i tried to extract the files using google collab and was thinking of accessing this course from the drive itself but failed to do so. Can someone help on how did you download these files from google drive and how do you extract such huge chunk of data?

Buy an external SSD(always useful), Expand Google drive if necessary for atleast 1 month, Copy to Google Drive and download, Extract

 

[rvins200]

How do you guys download such big files? i tried to extract the files using google collab and was thinking of accessing this course from the drive itself but failed to do so. Can someone help on how did you download these files from google drive and how do you extract such huge chunk of data?

U copy 15 gb then 15 gb and so on ...
After download whole course u going to realize why I download .
Go ahead.

 

[xiiiowl]

you are a legend man

 

[bawajpr]

Wow

 

[Lightning Storm]

hi @dikk
could you please compress this course for me! i cannnot download this course since its duration is too large hundreds of GB
thanks so much

 

[Nikpatel]

i like java full course of oanyone have

 

[hellodear]

Can you tell me how big is it? I imagine based on their website must be close to 100GB or even more. CHecked a few videos on youtube, speaks OK, and there seem to be quite a few projects after all that basic python, oop, numpy, pandas crap that by now anyone interested in ds / ml / ai should know at least fundamentally.

Anyway -- can someone tell us if it worth to grab it instead of the zero to hero pytorch | tensorflow | machine learning / data science course, or even the 365 datascience classes that seems to have very similar content? What difference this one makes compared to those? Well, not comparing that this course is bragging anout 500+ hrs of content.... (I'd say that is a drawback not an advantage - speaking concisely is a virtue, while blabbling for hours on end is not)

I will not download this, just wondering if someone amongst the currently ~100 people who intended to download this have some opinion about this. Well, after the download completes, so maybe a week later probably.

its 226GB after extraction.

 

[hellodear]

Hey, after the death of google workspace 1TB account, how are people generally downloading it? are you guys buying the google storage or is their a way to download it directly to the harddrive?

 

[hellodear]

So almost like a quarter terabyte? WTF is it like 4k videos for handmade drawings and talking heads or what?
Or this must be watched at warp-speed so someone could finish it in their lifetime

@Lightning Storm - sorry will not download, this is just insanely too much data for such a course.

The videos are 3-4 hours long therefore, the size. The course material is really good, it has live videos and the fast track courses inside. So if you want to speed up the process then just watch fast track course if you want the whole deal then go for live videos of 3-4hrs which I would recommend if you are a beginner. Explanations are sweet. And yeah you can finish it in 2-3 months Max.

 

[renderer]

You know what, I might take a look. though I prefer shorter more focused content, not 3-4 hrs long videos I tend to lose interest in half an hour or so. But I might take a look depending on how fast I can download it.

The only ones I find worth it is the DSAR section, where they discuss systems design and architecture of data science projects. The course indeed is a lot of value for a bootcamp, considering it's very cheap and covers a lot of ground, but unfortunately its live class-format gives it a lot of noise, 3 hours per video makes it hard to skim, find important content, and rewatch/review.

Usually the last hour of each lecture is dedicated to answering questions from the students. They also have lectures dedicated to just answering questions, they call these "doubt clearing sections."

Then they also include lectures from previous batches in the form of "fast track" sections, that students can go through if they want to study ahead of the live class schedule. This redundancy balloons the whole thing to being around 600 hours worth of video duration.

 

[renderer]

Thanks for sharing your opinion. I thought about it similarly like you. For me the ideal content is the one like the guy at fireship.io does. No need to crank up the playback speed at all I type the code, stop the video and maybe rewind a bit time to time. Very practical, focused content.

And about system design, isn't the byte by byte guy (Alex Xu) one of the best in that regard? Or are there like tremendous differences with how an ML project is scaled built-up compared to anything else?

Yes, Alex has a new book on ML System Design. I havent checked it yet though, as I dont work in ML. But the design discussion at ineuron isnt really about interview style system design, but instead about architecture and about defining engineering and design requirements. Thus I find it more practical for work. Although, the duration makes it hard to watch, the whole DSAR section is about 30 hours, where he tends to go off-tangent a lot as well.

As for the best in SD, Alex's books are definitely one of the best especially volume 2 of his book for junior-senior levels. For above senior-levels, say Staff or Principal, you'll have to supplement Alex Xu with more resources, particularly those that deal with implementation details to survive the deep dive sections of the interview. Arpit Bhayani (

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,

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) and Mikhail Smarshchok (

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) are the only Staff-level Software Engineers from big tech who make educational content about system design. If you like fireship, then you'll likely prefer Mikhail as his content is very compact. Both him and Arpit make practical and cost-effective system design, as well as dig into implementation details.

 

[akarsh_darkstar]

thanks

 

[rishabhkatiyar49]

G fdd

 

[prem9898]

i need fullstack datascience course link any one help me

 

[ruruvats]

great course

 

[mat24]

thank you for your work

 

[Harsha_123]

can u upload the course