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@Caughtinbetween I think @gouri03 can help you with this. She had a better knowledge overall.

 

No, I am sorry I don’t know anyone who has graduated from this program. Looks interesting though!

 

I do remember the program - when it started, it had quite a buzz because (a) it targeted PhDs and MDs in Boston / NY, and (b) it was fully paid for i.e. if you were selected, the program was free. Things are different now. I do not know anyone who has completed it, but here's a fellow who may respond to you (see bottom of his page): A Summer Adventure in San Francisco as an Insight Data Science Fellow

I took a quick look. Acceptance rate seems to be about 3-6%. Essentially you come in with a PhD (not mandatory, but ...) and data-science knowledge, and pay to be in a high-intensity job prep / job search environment.

If you are thinking about this, here are some random 'seed' thoughts to mull over, accept or reject:

(1) Intensive programs are useful because they compel you to concentrate and focus. You will be noticeably better at the end than you were at the beginning.

(2) In-person versions have the added benefit of camaraderie, collaboration, and contacts for the future.

(3) Such bootcamps cannot help beyond a certain point - it's a foundation, but given how much you have to learn, most of the top programs are probably more-or-less equivalent. So, find one that has a decent reputation and that may work for you. Don't get hung up on perceived prestige. The pandemic has had a leveling influence. Job guarantees, tie-ups with employers are useful to get that first employment break.

(4) The three most important advantages are the credentialing, the portfolio, and the employment connections. Otherwise, if you are disciplined, you can get pretty good on your own. There are excellent books and resources available for R, Python etc. Good stats and ML will need more effort.

(5) I don't know what your background is. Working solo, a somewhat science-y / tech savvy person can get comfortable doing useful data science things with R and Python maybe in two months each, working consistently. Do that before you join programs like this where you pay a fair bit of money. Use the program itself as a finishing school and as a way to generate a demo portfolio & a presentation, to get job connections and interviews. Don't go in as a newbie expecting to be taught.

(6) One prep option is as follows: work through a book or five in R and Python (R, ggplot2, modeling, H20/lime, Shiny - there, that's five). Then dream up some project that interests you. If you are short of ideas, consult someone in the industry you are interested in for things they think may be useful. Hire an online one-on-one tutor to help you finish your project. At $50 per hour, you could have a personal consultant for one project for $500. If you structure your work thoughtfully and plan ahead, you won't need more than ten hours of help.

(7) Now apply to Insight.

Rereading the above, I don't think I have really helped you, but I let it be anyway!

 

Excellent advice by @sokanasanah.

Not sure

This is great information from @sokanasanah.
I would suggest looking into coursera or udemy to start with R. Do you have a dataset that you can play with? When I learned R a few years ago, I took a short introductory course from coursera and watched online videos or asked someone on Academic Twitter when I couldn’t solve a problem. We mostly use R for graphs/ omics data representation.

There are many blogs dedicated for R
The 5 Most Effective Ways to Learn R

@sokanasanah is right. If you have science/tech background, it takes about a month to learn your way around and about 3-4 months to be able to do what you want to do. If you are a statistician, the learning curve might not be as steep as mine was.

If you aren’t on Twitter, I would suggest following Data scientists on Academic Twitter and network.

 

About what? OP wants to know!

 

I don’t know either. Fun of typing on my phone....

I didn’t see it and of course can’t delete now.