The Problem With Bootcamps

Happy Monday!

A new week provides new opportunity.

And if you’re looking to get into Data Science, you might think that’s via a bootcamp.

It makes sense - it’s like a degree but for a fraction of the time and cost.

I recently talked to somebody who completed a DS bootcamp.

I thought he’d have interviews lined up left, right and centre, but I was wrong.

He was also struggling to find a job, going through 100s of applications without a response.

Sound familiar?

After diving deeper into his problems, it was clear why.

Whilst the bootcamp had taught him some useful skills, they hadn’t considered the specific industries he wanted to work in when building projects.

This lead to him building a load of generic projects, which his dream employers didn’t care about.

Doesn’t sound like a recipe for success.

This made me think about the best way to build projects.

And it’s the opposite of how bootcamps do it.

You might say the answer is building industry-specific projects, but even that’s not enough.

A friend wanted to work in healthcare so planned to analyse hospitalisation rates in Africa.

But this wasn’t enough.

Why?

It wasn’t relevant to the problems his dream companies (based in London) have.

So you have to build projects which solve problems specific to your dream company.

This involves a detailed planning stage, where you define the problem and find relevant data.

Like Lekan did here:

Once you’ve planned the project, you need to execute it to perfection.

These types of project are central to my coaching program, the Confident Data Scientist.

Previous graduates have found a data science/analyst job within 3 months, increasing their salaries by $10k.

One of them is actually starting their new job today!

There are 4 more slots remaining for the program - but access closes tomorrow.

So shoot me an email if you’re interested in joining.

God Bless,

Albert