Four Reasons Why You Should Start A Data Science Blog



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4. Help others better understand the material

There are a ton of online courses that try to sell the idea that “Learn Data Science in 10 weeks or less,” “Cracking Data Science Interviews and earn you first million.”

This type of clickbait content is ubiquitous on the web, and beginners may be lost in the way of searching for the real stuff. So, my biggest writing motivation is to democratize Data Science by creating authentic content that is accessible to everyone.

My writing strategy is to do a thorough “literature review” of the existing works, spot the incremental value (i.e., the gap), and write a series of original posts on the topic.

Photo by Dominik Lange on Unsplash

Where to Start

Medium is the best writing platform that supports content writing. I enjoy reading and writing on the platform. It offers a flexible writing style, and its note-taking function is the best in the industry.

If you are a fresh starter on Data Science, try to write on topics like fundamental concepts, such as what is cross-validation in Machine Learning, what bootstrap is in Statistics, and other basic concepts.

If you are more experienced with these topics, try to take up more challenging topics, like writing on a hands-on tutorial, e.g., how to build a decision tree in Python.

Start with the most comfortable level with you and iterate quickly to the next level, which is the key to successful technical writing. My first blog post on the platform is unreadable, to say the least. However, my writing style has improved significantly over the past two years. Start small and iterate quickly.

Thanks for reading so far! If I have inspired you to write something, please let me know in the comment. I’ll give your first post a push on my social media (e.g., LinkedIn and Twitter).

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