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A Sure Way To Improve Your Data Science Skills

Improving our skills on Purpose

Photo by Austin Chan on Unsplash
Photo by Austin Chan on Unsplash

To date, I’ve gradually improved my Data Science skills based on gut feel. I’d feel as though I should have a better grasp of Algorithms then I’d study it and implement it from scratch in the Algorithms From Scratch series. In fact, this gut feeling was the same thing that brought about the PyTrix Series.

Not to say that I haven’t amassed tons of skills along the way because that wouldn’t be true. Nonetheless, there was a point I had reached where I began to ask myself why I’ve got all of these skills, fancy top writer acknowledgments on Medium, a rapidly growing network on Medium, and yet I still feel like I am just squabbling for scraps at the bottom of the food chain. My thoughts provided me with strong reflection points to meditate on during my meditation walks.

BAM! About 30 minutes into my Wednesday walk, last week, I was hit with an idea. No, not a spectacularly new idea that’s going to revolutionize mankind forever. It was just a simple idea that we all know about but quickly disregard – a bit like the broccoli. Deliberate Practice!

That was it.

"The surest way to improve my Data Science Skills was to practice them deliberately!"

For some reading this, you’ll probably think I’m just an over-excited kid just stating the obvious, and to be honest… It’s exactly how I feel!


What Is Deliberate Practice?

The term "Deliberate Practice" was coined by psychologist Anders Ericcson and it was used to refer to a special type of practice that is purposeful and systematic.

Every Practice session should have a focus.

As I figured from the development of my current skills, regular practice is simply "mindless repetitions". Performing this type of practice is okay for day-to-day activities like driving, cooking, or washing, but if there is something you really want to excel at doing, then there is a comfortability threshold you must deliberately push past to challenge yourself constantly.

Here is where deliberate practice comes into play. Deliberate practice is a technique used to improve at a skill of interest, based on constant feedback and working outside of your comfort zone. It requires there is a specific goal that one is aiming to attain and then the motivation to put all of one’s focus into attaining that goal.

Thence, we could define the components of deliberate practice into 4 sub-categories:

  • Motivation – Being willing to commit yourself constantly will require energy on the behalf of the practitioner.
  • Clear Objectives – Our goal must be clearly defined. We ought to know what it is we want to achieve by repeating our practice.
  • Fast Feedback loops – For us to improve we need rapid feedback and information on how we are currently performing.
  • Repetition – Constant repetition makes it stick!

Keeping these points in mind the most obvious way one could improve their Data Science skills is by taking part in Data Science competitions. I’m aware many people complain about competitions and how much they differ from real-world applications of AI/ML. However, I agree with competitors that say "competitions are a great way to become better problem solvers".

There are many platforms hosting Data Science competitions with Kaggle coming out as one of the most popular. If you are keen on improving your problem-solving skills with Machine Learning, competitions provide the best environment for this.

The act of attempting a solution for a problem and submitting your results to be evaluated on the Kaggle leaderboard serves as an instant feedback loop as you’d that you can use to measure your performance in accordance with other participants.

Note: there are other clear objectives you may seek to attain by competing such as improving your data storytelling skills.

Wrap Up

To become an expert on anything requires deliberate practice for prolonged periods of time. In this post, I’ve only suggested one way you can deliberately practice your Data Science skills, however, we already know (if you’re a follower of my post) that Data Science is a major field and there are bigger parts of the puzzle one can decide to focus on, for example, one may decide to focus on deploying models, or data storytelling. No matter what it is you decide to focus your attention on, deliberate practice will be a major feat if you want to stake a serious claim at your progress in the field.


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