Obi-Wan's secret weapon is the force.

Mine is the #tidyverse.

True story. 🧵

#rstats
It was 2014, and I was having a really tough time learning data science.

I was working on a project for work. Just sitting there staring at my computer...

Hoping the code would write itself.
I took a break to check my email.

Hadley Wickham, the biggest name in data science had introduced this new R package called "dplyr".

What's this? I took a look...
data %>%
group_by(player_id) %>%
summarize(total = sum(games_played))

Holy crap! I can actually read this!!

And, it looks good.

Just maybe this can help with my report.
Fast forward 7 years. (No, it didn't take me that long to make my report)

This dplyr package became part of a family of R packages called the "tidyverse".
And, I'm proud to say that to this day, learning the tidyverse helped me become really good at data science...

the very thing I used to struggle with.
My point is that we all run into problems like dealing with bad data, and the process can take years to get good.

And, if you would like help. Then I would like to help you.
I put in the painful years of learning data science the wrong way. So you don't have too.

And, I made a free webinar that will help.
It is 40-minutes of free training on the 10 secrets that took me 5-years to learn on my path to becoming a data scientist.

Literally what worked, and what mistakes to avoid in your path.

I cover all of it in one value-packed training.

Enjoy!

learn.business-science.io/free-rtrack-ma…

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More from @mdancho84

Aug 27
Stop learning data science.

Start learning how to solve problems.

Here's how... 🧵

#rstats #python #datascience
Most people dive into learning data science by taking course after course on:

coding,
algorithms,
math,
statistics,
computer science,
APIs,
web apps,
databases,
SQL...
And they learn
R,
Python,
SQL again (advanced this time),
Tableau (because I like dashboards),
PowerBI (because I realized my company doesn’t use tableau),
and…

You get the idea.

What a cluster…
Read 10 tweets
Aug 26
Shiny has a ton of new features that were just announced.

And I want to show off the 3 most important.

Here's how... 🧵

#rstats Image
Rstudio Conf 2022 dropped some bombs 💣

The week I spent there felt like a shiny whirlwind. 🌪️

But, now that I've digested, I'm ready to serve up the best of the best on a platter. 🧑‍🍳🍽️
The pick of my Shiny App transformation is 1 of the 3 amazing new features that I'll be demonstrating in my upcoming training.
Read 5 tweets
Aug 26
Why does every beginner data scientist fall for the "deep learning trap"?

#rstats #python 🧵 Image
When I was first learning data science this cost me at least 6-months.

Seriously...
I was building a model for predicting which quotes would become orders.

I had just finished using a linear regression (didn't know about logistic yet) to make a predictive model.
Read 14 tweets
Aug 15
In about 4-hours, I go live to talk about almost 1-year of research into the data science hiring process...

Here's what I'm going to cover...

#rstats
I spent almost a year researching the data science hiring process... And everything I thought I knew was wrong.

In this training, you'll learn...
1. What I found out from interviewing the data science hiring manager at S&P Global (Fortune 500)

He has had his hand in over 100 data science hires (not to mention 1000s of resumes & candidates)

He blew open their entire hiring process.
Read 6 tweets
Aug 14
Are you an #R User?

Are you seeking a 6-figure data scientist job? Good.

Then read this. 🧵

#rstats Image
I've recently tested several non-obvious strategies for getting data science jobs.

And 3 have show exceptional lift.

I'll talk about 1 of 3 today: the pitch deck.
You’re probably thinking why do I need a pitch deck?

Here’s why.

The pitch deck is the secret that helped Diana get her Senior Data Scientist position at a major Airline.
Read 12 tweets
Aug 7
The biggest lie is that companies want data science.

They don't.

Here's what they really want. 🧵

#rstats #python #datascience
Companies are hiring data scientists in droves for good reason.

But, it's not because they want data science.
What companies **don't** care about:

- Tools (#R or #Python)

- Math (sure it's important, but not the most important)

- Advanced degrees (e.g. Computer Science, PhD)

- Code (not important to them)
Read 8 tweets

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