Thread by @mdancho84

It took me 5-years to feel confident in data science.

True story.🧵

#datascience #rstats

This is coming from a person that has created two R packages that combine for 1.5 Million downloads.

Has trained elite data scientists at Apple, Walmart, Google.

And has built a career teaching students how to become data scientists.

Why did it take so long?

👉 Too many resources.

I thought I had to learn everything:

Deep learning.
Machine learning.
Algorithms.

The toughest part was figuring out which tools to learn and which were “red herrings” (a waste of time).

This cost me years going back and forth between R and Python...

Listening to too many people saying what they thought I needed to learn

(and finding out they’ve never actually done half the things they are telling me to do).

👉 Learning from bootcamps.

I learned a ton of skills but I never used 90%.

Worse, I didn’t know which 10% was actually useful.

Plus they didn’t teach some of the things that are absolutely critical.

I remember after my first bootcamp I struggled making a random forest because I didn’t know how work with features and format them right.

This left me confused and unconfident.

Set me back months.

👉 Researching topics too in depth before getting started.

I love learning, but there is a trade off with trying to master before applying.

Masters become masters by making lots of mistakes and learning.

Not reading about topics for weeks before applying.

I’ve since consolidated my learnings into 10 secrets that I wished I knew going into data science.

These are the 10 most valuable tools I’ve learned over my journey.

What's Your Next Step?

I have made a short 40-minute presentation on how to become a data scientist.

And remember, I’ve been there. We all start at the same spot.

👉Watch Here: learn.business-science.io/free-rtrack-ma…