
Writing about Data Science for two years teaches you a thing or two. 200+ articles on Towards Data Science alone brought me a lot of experience, insights, and money.
Today I’ll share with you a couple of eye-openers and gotchas when it comes to writing. Everything you’ll read is based only on writing about tech, programming, and data science. Points from the article might not be ideally suited for other areas, such as self-improvement and fiction.
Let’s start with a point that most software and data professionals get wrong.
You Don’t Have To Be an Expert, Just One Step Ahead
Writing blog posts isn’t the same as writing scientific papers. Yet, many fail to distinguish between the two.
You don’t need a Ph.D. to write a simple "how-to" data science post. All you need is to be one step ahead of your target audience. For example, if you aim to write about moving average models in time series forecasting, you need to know some basic theory, math, and code implementation.
Being the expert can’t hurt, but the views on your articles will suffer as soon as you get too deep into the math, proofs, and unnecessary theory. People reading your pieces are in a hurry and need a solution – fast. Blog posts aren’t books nor scientific papers. What makes the blog post valuable is your ability to summarize 100-page subjects into a 5-minute read.
Having that in mind, almost anyone can write a decent blog post on a technology they learned yesterday. I’m willing to go as far and say that beginners can be better at teaching than skilled professionals – as one beginner knows the struggles of another.
Take a look at your favorite online instructors. I’m willing to take a chance and say they have courses in 20+ areas. Are they necessarily the industry leader in all of them? No. But they know how to teach just enough so you’re comfortable to explore further on your own.
People Care About a Story, Not a Tutorial
But it’s much easier to write a tutorial.
Most of my articles that were based on a personal story or had some personal touch got anywhere from 5–10 more views and claps. The reason is simple – people can connect with your opinion and viewpoints but can’t quite connect with an emotionless "how-to" guide.
Writing a paragraph or two on how and why you’ve used some technology to solve a specific problem can establish an instant connection with the reader. On the other hand, a generic 3000-word article on the ins and outs of some technology will most likely make the reader go somewhere else.
Keep it short and simple, and add a personal touch. It’s harder than you think.
People Want Your Opinion – It Doesn’t Matter if There Are Thousands of Articles on the Topic
The title says it all. This point is closely related to the previous one. I’ve received at least a dozen messages asking how to come up with "original" article ideas.
The short answer is – you can’t.
Well, you can if you’re a creator of some library or a product. For everybody else, coming up with never-seen article ideas is near-impossible. Everything is already available and explained, either through the documentation or countless articles.
And that’s a good thing.
For example, take a look at my M1 MacBook series. The whole M1 topic is still hot in the news, even though the chip was released more than six months ago. There are thousands of similar articles online, but adding my opinion on the topic from a data science perspective brought hundreds of thousands of views and has wholly paid for my M1 MacBook Pro.
People want to read opinion pieces. Therefore, writing such articles will attract a similar-minded audience faster than any "how-to" guide will.
The Possibilities To Write Are Endless
The previous point discussed that trying to come up with original ideas is extremely difficult and pointless. Still, coming up with your first article idea isn’t easy.
Here’s an example of what you can do.
Let’s say you’ve written an article titled "Top 5 Programming Skills Data Scientists Need". It doesn’t have to be your article – it can be based on a piece you’ve found useful. Some of these skills could include data structures and algorithms, design patterns, and soft skills. Now what?
You could write follow-up pieces that go into more depth on each. For example:
- Why data scientists must learn data structures and algorithms
- Why data scientists must learn the basics of design patterns
- Are you a data scientist? Here are the soft skills you must master
The titles are a bit generic, but you get the point.
You can also go further by diving into each of the individual points. For example:
- Linked lists explained for data scientists
- A data science guide to recursion
- Searching and sorting algorithms explained for data scientists
Here, the key takeaway is explaining the well-known programming concepts to someone who doesn’t necessarily have a strong programming background.
And that’s how you can generate 10+ article ideas from a single article.
Once You Start Focusing on Stats and Money, You Start To Hate Writing
It’s nice to earn something on the side from writing. I’ve earned more by writing about data science than by working full time as a mid-level data scientist. Makes sense? Who can tell.
That can easily be you.
Back to the point. Once the money from writing keeps coming in regularly, it’s easy to get obsessed with stats and individual article earnings. That’s especially true on Medium, as their statistics panel is magnificent.
The only bad thing about earning a lot from writing is – you don’t want to quit or do it when you feel like it. Overnight it can become a second job you didn’t ask for. And like with any job, soon it starts to feel like just another thing you have to do before the day is over.
Trading time with loved ones for extra money isn’t worth it, and a couple of months down the road it can make you hate writing. That’s what happened to me when I tried to balance between a full-time job, writing 4–5 articles per week, college, and a relationship. If you can sustainably fit all of that in 24 hours and get a good night’s sleep, you’re a better person than me. Hope you don’t have a stroke at 35.
For me, a sweet spot is around 50 work hours per week. That includes a full-time job and writing 2–3 articles. Your mileage may vary.
Just don’t lose yourself, your health, and people close to you in the process.
Final Words
To summarize, writing 200+ data science and programming articles taught me that writing can be more profitable than a full-time job. I work as a mid-level data scientist, and an hour of writing is roughly 4x more profitable than an hour of the daily job.
The number likely won’t be the same for you. They are highly dependent on where you live and what sort of a job you do.
Still, writing two articles per week can bring a significant side income if you’re willing to put in the effort. The most challenging thing is to get started, so why don’t you do it right now?
Just don’t let it overwhelm you and keep you away from friends and loved ones. Time with them is something you can’t buy.
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