What is data science?

There are so many beginner, intermediate and pro data scientists out there who are sharing with the community by writing for data science blogs and or their personal blogs. Generally, their articles can either be technical or non-technical. A technical article is written to explain some technical concept usually with some code. In this article, I will attempt to convince you to start writing and give you some guidelines on how to get started.data analytics courses online

Let’s start by establishing why you should start writing:

Building a personal brand

This is true for data science as it is true for any other career path. When you write you establish yourself as an expert in data science. People on the internet will associate you with what you write about. When people think of you they see you in the light of what you write. This is a great thing for building your personal brand as a data scientist. Writing is a way for you to showcase your prowess to the world and acts as a silent resume for you. There are many publications such as Towards Data Science and Heartbeat that you can contribute to. The advantage of publishing with them as opposed to your personal Medium account is that they have editors who review your article before going live. They also give you feedback that helps you to improve your writing skills. The other amazing thing they do is help you to push your content online. This does go a long way in building your brand in this field.

Becoming a part of data science communities.

There are numerous data science communities on LinkedIn, Facebook, Medium etc. By writing you also establish a follower-ship of people who are always looking forward to your pieces. I was amazed when somebody contacted me on LinkedIn and informed me that they know me as one of the contributors to Machine Learning in our nation. It is so motivating to know that your work is providing value to people out there. By contributing to these communities you also put yourself in a position where getting help from the community becomes easy. This is because people see you as someone who is genuinely interested in the growth of the community. Data Science Online Training . Some publications also pay you to write for them, but if this will be your sole reason for writing I can promise you that you won’t last long enough in the game.

Mentor others

We live in a world that is a global village because of the internet. There are so many data scientists I look up to because of their courses and blogs. Although they may not know it they are mentoring me and so many other people who look up to them. In the same way, my work and yours can mentor other data science enthusiasts because now all connected. I believe the best way to learn is to look up to the people who have gone ahead of us, to work with the people we are at the same level with and to mentor those people who are still coming up. So what are you waiting for? It’s time to light the candle for the next data science enthusiast.

Pay it forward

There is a very big probability that you learnt what you know because someone mentored you, published a course or wrote a blog. In the same way, your work can support an upcoming data scientist to believe in the beauty of their dreams. It’s also a way to keep this community growing.

Door to numerous opportunities

When you write, your work becomes instantly available to the entire world. Anyone Googling you or looking at your profile can find your work. I started writing on my personal Medium account and later started writing for Towards Data Science. A community manager at one of the Machine Learning Blogs in Boston saw my work and contacted me via LinkedIn. They wanted to know if I would be interested in writing paid articles for their blog. So many people want to write for paid blogs but they don’t have a portfolio to show. Your articles will act as a resume for you when the opportunity presents itself.

Now that has convinced you that you should write, let’s go through a few guidelines that you should keep in mind.

Not everyone will read your article

It takes a lot of time to put these pieces together, but the truth is that not everyone who will come across your article will read it. With that in mind makes it easy for people to skim your article. Don’t write a monologue. Use sub-headings and then have explanations after them. If your subheadings capture the reader’s attention they will proceed to read further. Writing a long essay without subheadings makes it very cumbersome for a reader to follow through your article.

Use images when possible

We are visual beings. Images capture the reader’s attention. Use images to explain certain concepts. For example, if you are writing an article about decision trees an image of a decision tree would make it very easy for the reader to understand the concept of decision trees.

Use bullet points

Instead of counting down points in a sentence, do so using bullet points. Counting down points within a paragraph makes it very hard to follow an article. Using bullet points or numbers makes the structure of the article look nice and easy to follow.

Your code is the least important thing in your article

The most important thing is for the reader to understand the concepts. When they do so they can implement them using any tool available out there. As a rule of thumb, you should always explain before your code then interpret afterwards. Before you paste any code make sure you have explained prior what the code segment is going to do. Copy-pasting code without prior explanation makes your article hard to read and follow. Explain the parameters that a certain function is taking so that the reader has proper understanding. Don’t just explain things on the surface. Take time to explain concepts in depth. Don’t just copy-paste what is globally available on Google. Take time and research so that your articles offer real value to the reader.

Beware of the tense

If you are writing an opinion piece you can use words like ‘I’ and ‘my’. However, if you are writing a tutorial use words such as ‘Let’s’ . For example instead of saying I will now load the data set you should say Let’s now load the data set.

Some data sets have been overused

Data sets such as the Iris data set have been used numerous times. While there is nothing wrong with using these data sets, readers always want to see new things. Using data sets that come with packages like Keras or Scikit learn is also good. However, these data sets are already clean and rob the reader the chance to see how you prepare your datasets for data science. While it is not always possible to do this I can assure you that beginners are always looking for articles that show the full data science life cycle.

Get feedback from people before you publish

Asking for feedback before publishing helps to improve your articles before taking it live. It might help you to add some things that you and omitted or to remove some things that may be unnecessary.

Proofread your work.

This sounds obvious but it's very critical. It’s extremely difficult to read an article with spelling and grammar errors.

Don’t stop writing

You will be surprised to know that there are some people who are eagerly waiting for your next post, don’t disappoint them.

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Conclusion:-Writing is a skill like any other and takes time to master. All you have to do is to start. As you keep writing your skills will improve. So don’t give up if people don’t like the first post. I hope I have convinced you to start contributing to this amazing community of data scientists.