You should publish articles while you are learning - Why, How and Where

I recently wrote a guide that aims to cover everything that a learner may need to write and publish articles on the internet.

It covers why you should write, writing advice for new writers, and a list of places that invite contributions from new writers:

Why you should write:

Writing isn’t just for “writers”. The art of writing well is for everyone to learn - programmers, marketers, managers and leaders, alike. And yes, data scientists and analysts too!

You should write because when you do so:

  • You learn the art of writing and data skills better
  • You teach and make your reader’s learning journeys easier
  • You reach other learners and working professionals and thus, grow your professional network

Publishing your knowledge has a direct impact on your career as it often opens up unexpected opportunities!

Writing advice for new writers

If you have decided to take on the leap and start writing, I have a few pieces of advice for you. These are some simple tips that most new writers aren’t aware of. I learned some of them the hard way and now you can learn them all with ease:

  • Be mindful of your writing style
  • Be prepared to throw away a lot of what you write
  • Check for spelling, punctuation and grammatical errors
  • Submit every article that you write to multiple sources/publications if they allow “canonical URLs”

List of places that accept contributions:

Finally, when you have an article ready, you should try to publish it in popular publications so you may reach as wide an audience as possible. The article lists a full list of places that welcome contributions from beginners.

This was just a summary! You can read the full thing on Dataquest’s blog here:


Thanks a lot for this list so useful…

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Thanks for posting an updated guide. It is brief and clear.

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Thanks a lot very insightful

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@nityesh Thank you for your article! I agree with you that it’s a good practice to write post while we are learning (and after that). But in same time I struggle with fear to make mistakes in my writings. Do you have any piece of advise how to improve in writings? Maybe you know some sources to learn and train?

English is not my native language. I’ve learnt it mostly by myself in internet. So I can understand most video courses and youtube without any subtitles, can read articles (but sometimes translate some words. sometimes a lot of words :sweat_smile:). But to write is something that I didn’t do, and that’s why I’m so timid and unsure how to write correctly and in proper way. Will appreciate any help on that :slight_smile:


English is my second language as well but I was fortunate to have gone to a school where it was taught as a first language. Therefore, I can understand some of your fears but I cannot imagine the struggles of learning a language on the Internet.

I’ll try my best to help you with this.

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Thank you so much for your attention and kindness. Hope one day I will start to write articles, and help others too :slight_smile:

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It sounds like you agree with the idea in the article, that publishing your work can help you and others improve, but are hesitant to do so because you do not feel confident writing in English. Just a couple thoughts for you:

  1. Why do you have to write in English? if you feel like you want to write something, put it out there in your native language. who knows, maybe you could end up becoming the Data Science authority in your language just because you decided not to do what everyone else is doing. Imagine if when you began learning, you could have read articles written plainly in your language!

  2. If you decide to write in English your English will also improve as well as your DS skills. You will make mistakes. People will be jerks about it. But, if you are presenting good ideas, in a clear way, to an appropriate audience, most people will be appreciative and helpful.

  3. You could either have someone help you translate your work, or have an English speaker go through and edit it for grammar and clarity.

good luck!

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