This guide aims to cover everything that a data science 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.
Let's get to it!
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 articles because when you do:
Writing teaches you the art of writing. It's kind of circular but it's true.
Make no mistake, the art of writing isn't about grammar (although, that's important) and flowery language (definitely not important). It's about conveying your thoughts with clarity in simple language.
And learning this art is important even if you absolutely know that you don't want to write blogs/articles for a living. It's important because all the jobs have some form of writing involved - messages, emails, memos and the whole spectrum. So basically, writing is a medium for almost any job you can have.
Apart from that, when you write you learn the things that you thought you knew but didn't really know. So, writing is an opportunity to learn better.
When you write, you share your specific experiences with others.
That is also why you have all the reason to feel confident that you have something important to contribute, regardless of your expertise. You have a story and you can say it. Tell them how you learned, what you learned, and where you learned. Tell them about all the lessons that you learned with difficulty. Tell them about all those hard-earned moments when you really understood a complicated concept.
You can write articles and blog posts to share these experiences with others so that they can have it easier than you did. And of course, you get the gratification in knowing that you eased your readers' learning journeys!
When you write your story, you can potentially reach thousands of people. It's an opportunity for you to build your own audience. An opportunity to build your own following. An opportunity to "make your name" in the field. How exciting is that!
And it's not just thrills and excitement. Remember, working professionals are learners too; learning on the job is a real thing. This means that many times, the people who read your articles will be working professionals. Helping them means that you get to build and grow your professional network!
Writing can help your career:
Every time you publish some of your work, you're increasing the chances that a potential employer or client is going to come across it and get in contact. You might be surprised by what unexpected opportunities can arise when you simply put your work in front of others.
Written articles can also be great to include on your resume. After all, working in data science isn't just about having programming skills! Being an effective data scientist means being able to communicate clearly and effectively about data. Having published work on your resume is proof of your data communication skills.
Writing advice for new writers:
Hopefully, the last few paragraphs have motivated you to write.
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.
Here they are:
- Be mindful of your writing style. All learner-facing content should, first and foremost, feature a tone that is warm, welcoming, inclusive, encouraging, and friendly. Data science is especially complicated and it can be intimidating. The less intimidating you make your writing, the more people it reaches.
- Be prepared to throw away a lot of what you write. The most used key on a writer's keyboard is the
Backspacekey. So, don't be afraid to rewrite it if you have to.
Reread it. Delete it. Replace it.
- Check for spelling, punctuation and grammatical 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.
- Submit every article that you write to multiple sources/publications if they allow "canonical URLs".
This is called cross-posting. Cross-posting helps your article reach multiple audiences - and as a new writer, you need to reach as many eyes as you can.
But remember, cross-post only to a website that allows you to set "canonical URLs". Search engines use canonical links to determine and prioritize the ultimate source of content, removing confusion when there are multiple copies of the same document in different locations. Sites that publish an overabundance of duplicate content without indicating a canonical link may be penalized in search engine rankings.
List of places that accept contributions:
When you have an article ready, these are some of the very popular places that will accept your writing and share it with their huge follower bases:
- Medium publications
- Hacker Noon
- Analytics Vidhya
- KD Nuggets
It is extremely important that you carefully read and follow the advice that the place you are submitting to has laid out.
We hope this guide has helped you in your writing journey! If you've found your time with Dataquest helpful, we'd love it if you mentioned us in your article so that other learners can find us, too! 🙂