Learning to Code in Data Science is Hard

I am constantly finding myself asking, "Why am I learning to code in Data Science?" And not just once - but every time I sit down to study or work on a project. I've learned that I'm not alone here. This is a pretty common question among people who are new to the process of learning how to code from a non-technical background.

When you first start coding, everything seems impossible and you make a lot of mistakes

When you first dive into coding, it can be overwhelming. One of the toughest things to do is to wrap your head around the artificial syntax of programming languages and determine an efficient way to put all your ideas and creativity into code. Every mistake is a learning experience – by thinking more critically, and figuring out what went wrong with each error, you slowly get better and closer to mastering the language. Even when coding feels like an impossible task, plugging away and seeing that creativity come to life through perfecting lines of code just makes every misstep worthwhile.

The key to success is consistency - keep practicing even when you make mistakes

I've heard the saying 'practice makes perfect' enough times, and it couldn't be truer when learning to code. But what many don't realize is that even mistakes can be a valuable part of the journey towards achieving success. The secret ingredient to making sure goals are reached is to stay consistent in your efforts, no matter how many times you stumble in the process. Making mistakes carries an incredibly high potential for learning and growth - so remember, don't give up when you find bumps in the road, just keep pushing forward with consistent action.

Focus your attention only on learning code, don't try to learn new topics for that period of time

I've learned that my ambitions get the best of me.  Temper the urge to learn everything from the start, no one becomes full-stack right out of the gate. It's important to zero in on the things you truly want and need to learn instead of trying to learn multiple topics at once. Rather than trying to cram a few different coding topics into one learning session, focus on honing and refining your skills with just one language.

For example, I'm currently struggling with JOINs in SQL.  The primary and foreign key concepts are flying in and out the window for me, therefore I'm doubling down on these and watching several YouTube videos, and reading articles solely on this topic.  This is slowing down my learning plan, but it's important to lock in my understanding here before I go on.

This process allows for deeper understanding and mastery if you tackle only one topic at a time. Of course, it may seem more efficient or faster-paced to multitask and learn various code languages all at once - however, this approach can often lead to feeling overwhelmed and even unfocused. So, if your goal is laser beam like concentration on coding knowledge quickly without getting frazzled and frazzled out - focus your attention only on learning code and don't bother with any new topics temporarily.

No one memorizes every line of code learned, you will always google the answers

I've learned overtime that when working in any form of the tech industry, it's impossible to remember every single line of code we learn. Learning to code doesn't just mean becoming a master coder who can write the most complex of codes by memory. It's about using the coding skills you have to ask yourself better questions and become a more thought-provoking data professional.

By understanding the code, you can begin to see certain patterns in data that may be getting overlooked or misinterpreted, as well as find creative ways to search for new data and insights. This understanding of both coding and data also helps hone problem-solving skills - after all, it’s not just about memorizing code, but also thinking outside of the box to come up with creative solutions and uncover underlying issues. In short, learning to code isn’t just about being a coder, but it can help you become a smarter and more intuitive data professional.

Coding can seem really daunting when you're just starting out. It's easy to get discouraged when you make a lot of mistakes, but the key is to be consistent and keep practicing. With time, you'll start making fewer mistakes and coding will become more fun as you learn more about it. Remember that everyone makes mistakes when they're learning something new - the important thing is not to give up.