Important question to all aspiring data scientists out there…

What’s the difference between Successfully-Working-as-a-Data-Scientist Guy A and Frustratedly-Watching-Data-Science-Youtube-Videos Guy B?

<<successful data scientist vs guy drowning in textbooks>>

IF YOU GUESSED…

how many hours invested in learning.

You’d be wrong.

how many thousands of dollars spent on a professional data science coach.

You’d be wrong.

A super fancy pristine PhD in Mathematics from MIT.

You’d be wrong.

But back in 2016, I thought the exact same.

I thought that studying more, paying more money, reading more textbooks made the difference between becoming a data scientist or failing.

In 2016, I was a fresh college graduate baby… and had 0 idea what I wanted to do in my life.

No work experience. No data degree. No clue what I needed to learn.

Now, 5 years later…

Fluent in Python. Fluent in SQL. Working as a Senior Data Scientist. Written 4903 machine learning algorithms. << share cool data words and results >>

How did that happen?

Let’s break it down.

In 2016, I made that proud declaration that I’m sure many of you have made: “I want to be a data scientist!”

Then I made the not-so-proud inquiry right after: “Um… now what?”

I started attempted to learn.

When I first started learning data science, it felt like I was beginning a puzzle with 4,593 mismatched pieces…

Oh, and I lost the puzzle box so I had no idea what the image is supposed to look like.

I tried endless Youtube videos and playlists.

I tried blog posts.

I tried all the normal data “schools”.

It didn’t stick.

So I was just sitting on the floor, kind of putting pieces of the puzzle together…

haphazardly…

and then wondering what I was doing wrong.

<<comic of dumb puzzle>>

And if you’re feeling a bit of the same…

Guess what?

It’s not our fault. / We’re not doing anything wrong.

Because in one fall afternoon in 2016, I stumbled across…

That was my epiphany.

I realized what was wrong. The way I was learning was wrong.

So if you’re there, I’m with you.

And I’m sorry.

I’m sorry that…

… that

On behalf of all those failed attempts that were not your fault, I am sorry.

And I’d love the opportunity to show you a better way.

Because learning the right way should be the antithesis of that.

Once I had my epiphany, I realized I had to approach this task differently.

The Proven 3-Step Path to *Real* Job-Ready Data Skills (and feeling confident enough to add “Data Scientist” to your Linkedin headline)

Step 1: Learn the Right Things

The reason most XYZ give up on their data journey is they’re trying to learn absolutely everything.

That’s a no-go.

I know it seems like being a data scientist is secretly being a jack-of-ALL-data-trades… like:

<< List out all the things they think they need>>

It’s not only NOT true, it’s also highly ineffective and inefficient to try to learn everything.

The reason this belief doesn’t work is:

<< When you try to learn everything, you often end up learning nothing plus with a side special of feeling too overwhelmed.

It’s like asking a musician to learn every single instrument instead of focusing down and becoming a master at their craft.

Becoming a data scientist requires careful prioritization.

Focus & learn only what you need to.

You can learn all the bells and whistles (or in this case, <<>> and <<>>) later.

For now, focus on the core 8 essentials.

I spent a lot of time distilling the contents of becoming a well-rounded data scientist down to the pure essentials in a step-by-step way.

Meaning:

<< List out DC curriculum >>

With these, and in this order, you can succeed.

Step 2: Learn the Right Way

Second – if you’ve been trying to DIY the data journey, you’ll know this struggle like the back of your hand.

Youtube videos.
Stack Overflow.
Random blog posts.
Code repositories.

What do they all have in common?

They are all fun and games until you’re 16 hours in on page 39 feeling like you have gained absolutely no new knowledge and are left feeling more confused than ever.

The reason they don’t work is:

They don’t teach you the concepts and applications in a step-by-step, practical, & holistic manner.

They give you small, random, theoretical pieces – it’s like someone chucking tiny, random pieces of your big data puzzle at you, without explaining how all the pieces fit together.

Sometimes – you’re not even sure the pieces that they’re throwing at you are even part of the same puzzle. It’s chaos.

<< comic >>

On top of that, they’re not even showing you how to apply your new skills. They aren’t showing you how to use it on the job either.

Nothing is practical. Nothing is hands on.

It’s all theoretical.

“Ideal” situations.

This tripped me up big time when I first started working as a data scientist: the act of applying the knowledge that I learned from textbooks.

And I don’t know about you but the chaos of entering a job and realizing you’ve literally never applied any knowledge ever before… is… horrifying.

<< comic >>

You need to apply your skillset.

Download practice data sets.

Find real, life exercises that data scientist actually do, not << >>.

Step 3: Learn with the Right People

And finally, something I didn’t really realize I needed early on was a community of supporters.

A community to hold me accountable to continue in my ambitious journey.

I highly recommend finding your tribe on Linkedin, Facebook, Instagram, Reddit, Stack Overflow or in your local communities.

Here are a few of my favorites:

<<comic of people helping behind one guy>>

That’s why I created Data Checkpoint, because I wanted to do it all differently.

The 3 steps above is how I designed the Data Checkpoint membership.

Data Checkpoint is the complete puzzle box.
Data Checkpoint comes with clearly labelled, numbered, step-by-step pieces.
Data Checkpoint comes with a private Slack student community.

Simple. Guided. Logical.

I included exercises upon exercises.

And you know what? These exercises are actually realistic on-the-job exercises, not “ideal” situation exercises.

We have communication channels in Slack for each mission included in Data Checkpoint depending on what you want to focus on, plus introductions and wins to guide you along the journey.

Ask for help when you need it as a beginner.

Give help when you’re further along in your journey.

We’re there for you.

<< Credibility logos or something >>

So if you’re ready to *finally* become a data scientist in a no-fluff, job-ready, guided and practical way…

I’d love to invite you into Data Checkpoint.

We have two plans – $37/month or $197/year.

I can’t wait to welcome you in.

Join button.