How to Start Your Career as a Data Scientist with Python?

This guide is a conceptual view on how to start your career as a data scientist–and on which skills you should focus.

Here are the three most important steps recommended in the video:

  1. Learn Python basics (link to free Python crash course on this blog).
  2. Learn NumPy (link to free NumPy tutorial on this blog).
  3. Learn TensorFlow (link to TensorFlow project).

So the most important thing you can do is to master the basics because your knowledge will become more generalizable. Learning any more specific skill (moving up the stack) will become easier.

How to Earn Money as You Master The Stack?

Today, it’s simple (but not easy) to get paid for learning and improving your skills.

And it’s dangerous not getting paid for learning: you’ll not be able to compete in today’s marketplace.

Why? Because other people who get paid for learning the skill can invest much more time and effort into training. If you don’t get money for learning the skill (assuming you don’t have enough money in the bank to pay for the learning time yourself), it’ll be extremely hard to carve out learning time in the evening hours when you’re already exhausted from your day-to-day job.

Seek Quality Time

So how can you earn money as a beginner coder? One tip that helped me hone my Python skills two years ago was to polish my practical skills as a Python freelancer. Working from home (even if it’s part-time from the side) gives you flexibility. As a freelancer, you’re forced to learn state-of-the-art skills for which the marketplace is willing to pay money now.

Besides honing your technical expertise, you’ll improve your business skills learning accounting, marketing, and selling in a controlled environment.

And there are plenty of freelancing jobs for data scientists–from beginner to advanced level jobs.

If you believe that becoming a Python freelancer is for you, check out my Python freelancer course!

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