137: Get PAID $1000s to Master Data Analytics Skills in 2025?

Avery: 00:00:00

So you want to be a data analyst.

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Well, there are three main ways

that you can learn to become one.

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Number one, you can learn for free.

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Number two, you can pay to learn.

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And three, my personal favorite

is to get paid to learn.

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And in my opinion, this

is the best option.

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I mean, who wouldn't want to learn?

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To get paid to become a data analyst,

but it might seem impossible, right?

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But in today's video, we'll discuss how I

did that and how you can do the same, but

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let's start with ways to learn for free.

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There are lots of really

cool ways to learn online.

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And if you're listening or watching this

on YouTube or via your podcast player, you

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found the two best resources in my mind.

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YouTube and podcasts are free

education that honestly, A lot of

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the time are better than the Ivy

league educations, in my opinion.

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So if you enjoy learning for free and you

enjoy learning on YouTube or via podcasts,

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go ahead and hit that subscribe button.

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Subscribe to my channel because every

week I am putting out free new data

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content and it'll help you learn.

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Now, of course, there are other

resources like Khan Academy or W3

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that will help you learn as well.

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These have pros and cons.

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The pro is it's free

and it's easy to access.

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The cons are obviously there's not

really any help if you get stuck.

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And some of the material can be a

little bit superficial sometimes.

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And if you're feeling that way, well

then of course you can pay to learn.

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There are so many ways to pay to learn.

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The number one way probably is

by getting a college degree.

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In the past for data, most of the

college degrees were like master's

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degrees or PhDs or something like that.

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But now there's a lot of undergrads in

data science and data analytics as well.

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These routes are probably going to be the

most expensive and they're going to range

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probably from 20, 000 to maybe 60, 000.

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There are some degrees that are going

to be a little bit less, but regardless,

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this is a pretty expensive decision

because you're going to be having a

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professor, you're going to be having TAs.

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You're going to be on campus a lot

of the time, and it's just pricey.

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Then, of course, there are boot camps.

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A lot of these boot camps are going

to range between 10, 000 to 30, 000.

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It's basically like a college experience

packaged into a 6 to 12 month experience.

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A lot of these are going to be

from universities, but they're

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actually not ran by the university.

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But they can be just fine, but unless

you do a bootcamp like mine, the data

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analytic accelerator, that's affordable,

it's going to be quite pricey.

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If you want to check out my bootcamp, you

can look in the show notes down below.

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I tried to make it as good as a regular

bootcamp, but at a fraction of the price.

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Then of course, there's the Google

data analytics certificate or the IBM

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data analyst certificate or whatever.

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There's all these different little

mini courses that you can take.

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These are obviously a lot

cheaper, but once again, do

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not have any of the hands on.

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So you're kind of back to the free boat.

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It's just like premium free, basically, at

that point, I don't actually recommend the

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Google data analytics, sir, or the IBM,

sir, because I don't think they actually

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teach you all that much useful stuff.

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Sure.

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It's good stuff, but

they give you too much.

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It takes too long and they're

not teaching you the right stuff,

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but that's for another video.

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Let's talk about getting paid to learn.

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What do exactly do I mean by that?

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And here's the truth.

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It's going to be pretty rare for

you to get paid to learn data unless

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you are employed in a data position.

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And that kind of seems like a chicken

or the egg thing where it's like, or

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how am I going to get paid to learn

data unless I have a data position?

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Well, I did a position.

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I probably already know data.

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And that's only half true.

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The truth is there's actually lots of

data jobs where you don't have to know.

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All that much.

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You definitely have to know something,

but you don't have to know everything.

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So it's like, there's data jobs

out there where you only have to

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use Excel, or you only have to use

Tableau, or you only have to use SQL.

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You don't need to learn Excel,

SQL, Tableau, Python, R,

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JavaScript, Power BI, SAS.

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all these different tools,

it's not going to happen.

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It's impossible to learn all

those things and it's going

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to take you way too much time.

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So instead you can just learn the basics.

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You can just learn one and then get paid

to learn the rest of those on the job.

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And you might be thinking,

Avery, I don't believe you.

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Like how the heck, why are these

companies going to hire me?

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Why are they going to pay

me to learn these things?

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And it's actually very

common in the data industry.

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Companies want their analysts.

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To learn and improve.

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And it's really a win win for everyone.

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If you want to look at it optimistically,

it's very positive for them because you

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are improving and they're excited to have

you improve and they're excited for you

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to continue to add to their organization.

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If you want to look at it cynically,

you can think of they're hiring

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you underqualified and they're not

going to pay you as much because you

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don't have all the requirements or

you don't have all that experience.

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And it's actually cheaper.

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To hire you and train you than

it is to hire someone who already

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knows and who's already qualified.

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They're just not going to bump you up

nearly as much when you get qualified

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as they would hiring qualified.

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That's a cynical way of looking at it,

but either way you want to frame it.

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These companies want to teach you.

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They want to help you improve.

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And the truth is, if they didn't,

they would be screwed to be honest,

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because data is always evolving.

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Like it is impossible.

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To be in the data space and stay stagnant.

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If you stay stagnant, if you don't

learn, you're going to fall off.

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And data is money.

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They can't afford to not be performing

well in their data analytics division.

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So they're going to help you learn.

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So let's talk about the three

different ways that they're going

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to help you learn on the job.

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Number one, companies

will pay for your courses.

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And this can happen in a

couple of different ways.

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When I worked for ExxonMobil,

they honestly paid for

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my learning all the time.

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A very simple way that they'd pay for

my learning is everyone at the company

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has a LinkedIn Learning account.

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Basically, Exxon pays LinkedIn a

bajillion dollars a year for all of

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their employees to have unlimited

access to all of LinkedIn Learning.

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So instead of paying whatever the 40

bucks a month it is to have access to

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LinkedIn Premium, including LinkedIn

Learning, you get that for free.

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So when I was at Exxon Mobile, I took a

Power BI course, I took a stats course,

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I didn't have to pay for any of them.

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They'll also pay for maybe

like in person training.

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So actually when I was at Exxon

again, I had the opportunity to go

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to downtown Houston and attend a two

day seminar from the godfather of

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data visualization, Edward Tufte.

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In that training, I actually got all

four of Edward Tufte's books, and I

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actually got to hear from him and learn,

and I took so many notes, and I became

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so much better at data visualization.

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And I didn't pay A dollar for

that training and actually

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when I was at the training, I

still got my, you know, salary.

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It's not like I had to take off

work to go to that training.

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It was absolutely unbelievable.

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Way number two that a company

will actually pay you to learn

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is they'll pay for a degree.

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A lot of the times this will be

a master's, but sometimes it can

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be a bachelor's degree as well.

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So this happened to me when I was at

ExxonMobil, they helped pay for my

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master's in data analytics, even though

I already had a data job, they were

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encouraging me to continue my education.

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This actually occurred with one

of my students, Rachel Finch.

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Let's listen to what happened to her.

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You have a pretty fun announcement

in your learning journey as well.

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You want to share with the audience?

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Yeah.

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So I started my master's in analytics

just a week ago now through Georgia Tech.

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So I will be taking that

journey for a while.

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But I'm really excited about that too.

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And that was one of the, you know,

negotiation points is after six months,

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my company gives a really large stipend

towards education, which was just like

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what I would have had at Anheuser Busch

is just a fraction compared to this.

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So it really am getting paid to learn

that and in downtime on my job, they

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promote like the LinkedIn learning

courses, get to watch a bunch of

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tutorials and Tableau and Power BI.

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So.

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Really what you say about getting

paid to learn is such a big thing.

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Avery: And this is totally common.

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A lot of the times companies

will pay for master's degrees.

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A lot of the times you have to stay

at the company X amount of years to

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get that full tuition reimbursement.

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But this is a great option, especially

if you want to get a master's degree.

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The third way that a company will

pay you to learn on the job is

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you just will learn on the job.

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Like that's just part of it.

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Like you cannot do your

job without learning.

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And so I'm actually kind of embarrassed

to admit this, but when I started my

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data job, I didn't know SQL at all, but

obviously I had to figure out how to use

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it because they were using it on the job.

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And so I kind of just figured it out.

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Like I had some, my teammates helped

me and show me, Oh yeah, this is

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how, you know, you write SQL code

and your teammates, your peers,

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they're more than willing to help.

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And of course you can just use Google,

any of the free resources that we talked

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about earlier to be learning these things.

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Instead of learning them on your own

time and on your own dime, you're

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learning them at work, at a work

computer, at your desk, on work hours,

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and man, that clock is ticking and you

are making some cash along the way.

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So all this to say, my philosophy

is let's get your foot in the data

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door as quickly as possible by

only learning the bare minimum.

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Minimum, the basics, because you can

spend the rest of your life learning

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Python, learning machine learning,

learning D3, learning data visualization,

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whatever it is, mastering SQL, even

like that stuff takes a lot of time

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and you don't have a lot of time.

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You don't have a lot of money.

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We got to get you in making more

money as quickly as possible.

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So that way you can

provide for your family.

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You can spend on yourself, treat

yourself, go on a vacation.

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Like we need you learning on the

company dime as soon as possible.

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And the way that you do that.

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is by learning the bare minimum

and landing a data job as quickly

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as possible and then getting paid

to learn the rest on the job.

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That's actually my whole philosophy behind

my bootcamp data analytic accelerator

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is like, I want to teach you the bare

minimum that you need to land a job.

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So we focus on Excel, SQL, and Tableau.

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We build projects, we focus on

networking, and we're trying to get

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you a job as quickly as possible so

you can learn the rest on the job.

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If you're thinking, Avery,

how the heck do I do this?

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I understand.

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I want to do it, but how do I do it?

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Well, I have good news.

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I encourage you to sign up for my

free data career newsletter, where

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I share strategies on how to do this

every single week, all for free.

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And if you're ready to start learning

the basics, I suggest that you start with

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this episode here on what data skills

you should know and how to get started.

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I'll have that linked in the

show notes down below as well.

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Good luck to you guys.

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And let me know how I can help

in the comments down below.

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