1 like = 1 free extra day - Announcing a 2-month Dataquest Writers Challenge!

Hey folks!

Being able to write well is a superpower that can give you immense leverage in your career.

Especially in 2021!

And what better way to learn this skill than by publishing articles on the Internet!

Writing articles can have a huge impact on your career:

  • It can help you stand out in this competitive job market.
  • It can help you connect with data professionals from all over the world.
  • It can also bring job opportunities to you

We, at Dataquest, recognise this.

Therefore, I’m excited to announce a 2-month long Dataquest Writers Challenge! :tada:

Dataquest Writers Challenge

What is it:

A 2 month long (January-February) writing challenge where we invite every learner to write an article in our magazine - Dataquest Direct.

To encourage you, we are offering:

  1. Guaranteed eyeballs on your articles - We will share your articles with our own audience of 200,000+ data science enthusiasts. So you don’t need to worry about writing in the void!

  2. Extra days of Dataquest for free - For every like that your article gets, we will offer you one extra day on your Dataquest subscription for no cost to you!

How to submit:

Here are 2 ways you can submit your article for review:

  • Head over to Dataquest Direct and click “New Topic”. Then, write your article and hit the Submit button.


  • Send me the draft over email on nityesh@dataquest.io. You may use Notion or Google Docs to write the draft.

I will then review your draft, give you feedback and reach out to you for next steps.

What can I write about:

You can write about anything even remotely related to Data Science.

But if you’re feeling lost, here are some ideas:

  • Write better explanation for concepts that often trip learners. As a learner, you are in a favorable position that allows you to empathize with the problems of other learners like you. Write an article to solve that problem.
    If you are a @learning_assistants or a Community @champions, try to expand your existing posts into standalone articles. You already spend a lot of time engaging with Data Science learners. So, you are in the best position to understand which concepts often trip them.

  • Found a useful topic, tool or library that we don’t cover in our courses? Write a “how-to” or a “getting started” guide for that.

  • Tell us about all the lessons that you learned with difficulty. Tell us about all those hard-earned moments when you really understood a complicated concept.

  • Tell us your story. All of us are hungry for stories. Tell us about your learning journey, tell us about your motivation and tell us about your successes and failures.

  • Did a cool project? It’s a great idea to walk us through it - tell us what inspired you, the difficulties you faced, show us some code snippets and share what you learnt.

Our Submission Guidelines:

Here are a few guidelines that we expect you to follow when writing your articles. These guidelines are there to ensure a good experience for the readers:

  1. The first one is obvious - you should only share articles that you have written yourself. Don’t plagiarise.

  2. Add a cover image on the first line. Humans are visual creatures and adding beautiful, relevant images to your article makes it easier to read.

    But beware of copyright infringement. Don’t add images from Google Search.

    Do not use images (including logos and gifs) you found online without explicit permission from the owner. Adding the source to an image doesn’t grant you the right to use it.

    Use Unsplash or show off your data analysis skills by creating a pretty visualization using your favorite library.

  3. We only accept articles with a read time of 3 minutes or more. That’s about 800 words. If yours is less, dive deeper into the subject until you have more to speak about it.

  4. Be mindful of spelling, grammar and punctuation errors. Having a wide vocabulary is not important but using correct grammar is. You need to be extra careful if you aren’t a native English speaker. Using tools like Grammarly can help.

  5. Format all code using Markdown - no screenshots.

  6. Don’t use clickbaity titles (like “You won’t believe what happens…”).

Looking forward to seeing your submissions!

If you have any questions or need any help, feel free to reply here or send me a private message.

You can also check out this article for my advice to new writers.

All the best!


Any specific limitations on what we can write about other than what you have suggested above?

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Nope. Anything even remotely related to Data Science works @the_doctor!

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