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Boost Your Data Science Career

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Boost Your Career

Sign up for exclusive access to proven data science tips.

Do you want to learn data science faster?

 Well of course you do, your time is valuable.

The real question is, how do you do it?

There’s hundreds of online courses and textbooks.  Not to mention expensive degrees that could take you years to complete.

And guess what?  At the end of that, you probably still won’t have a data science job.

Instead of taking the long route, you should take the smart route.

I used this process and got a data science job offer in 3 months.

 

data science job

This wasn’t a normal job offer either, it was an offer to actually teach data science!

Not only was I offered a job, but because I used this process so effectively, I was regarded as an expert, immediately!

data science job offer
Now am I saying these results are going to be typical?  No.

Will it be easy to get a data science job right away?  Definitely not.

BUT…

If you’re willing to:

  • Put in the time
  • Take a smart approach
  • Engage in the data science community

I’m 100% sure it will work for you!

So how do you optimize your approach?

The way most of us are taught to learn is useless.

How often have you tried reading a textbook chapter front to back, and then given up after only a few pages?

Or even worse, you manage to read the entire chapter, but after a couple of days you can’t recall what you learned.

Here’s an optimized approach:

  • Pick a topic
  • Build a project
  • Document and share your work

For example, you might want to learn logistic regression.

Next, do a quick Google search on “logistic regression simple explanation”.

logistic regression simple explanation
A great resources is the simple version from Wikipedia. This provides a great explanation without a lot of mathy jargon.
logistic regression on wikipedia
After your search, you should be able to answer questions such as:

  • What is logistic regression?
  • What is it used for?
  • What are some typical applications?
After you have a basic understanding, start building a project.

You should have some ideas after you figure out what are some typical applications.

If you’re still unsure, Google “logistic regression” + dataset.  That will give you plenty of ideas.

Want even more project ideas? Check this out 

Want even more project ideas? Check this out!

To build your project, use Python or R.  Both have great machine learning libraries with plenty of documentation and examples.
python machine learning library
Don’t worry about capturing every single detail, this is just a quick project to get you started.

Don’t spend more than 8 – 10 hours on it.

As you continue to build projects, you’ll naturally start developing your data science skills.

You’ll be amazed at how quickly your projects become better and better as you keep building.

After you’ve built the code for your project, document it using a Jupyter Notebook or Rmarkdown.

These are great tools because you can document your projects in Markdown format, which can then be used to build a portfolio website.

python jupyter notebook
Github allows users a free static website using Github Pages. This is a perfect way to document and share your work.

These Github Pages use static website generators such as Jekyll.

Jekyll allows you to upload your project to your Github Page in Markdown format, and then automatically converts it into a static site.

github pages jekyll

After you’ve put your project on your portfolio website, it’s time to get the word out.

Make sure you link to your projects from LinkedIn.

 

linkedin project section

You should also include relevant projects on your resume.

Another great way to showcase your work is through guest-posting on data science blogs and newsletters.

Now that you have a basic blueprint, make sure that you sign up for our exclusive newsletter.

We’ll provide data science tips that will help boost your skills and improve your career in 2018.  Let’s get started!

 

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