Data science writing timeless lessons

Derrick Mwiti
Derrick Mwiti
2 min read

Table of Contents

This is my 6th year writing about data science and machine learning. It all started in 2018 when I submitted my articles to Towards Data Science. After publishing a few articles, I was contacted by a leading publication to create content for them. Before that, I had no idea one could be paid to write. I was only writing to build a brand in the data science space.  

Since then, I have had the opportunity to write data science and machine learning content for various companies such as:

  • Digital Ocean
  • Paperspace
  • neptune
  • Layer AI
  • Activeloop
  • Saturn Cloud
  • cnvrg
  • Neural Magic
  • KDnuggets mention a few.

There are unforgettable lessons I have learned after writing about data science and machine learning over the last 5 years. As we begin the year, I want to share 3 of them with you. Hopefully, they will encourage you to embark on writing about data science and machine learning this year.

Lesson #1 It will cost you sweat, blood, and tears to get good at anything, including learning data science and writing about it. Focus on building a writing habit, don't focus on the outcome. Focusing on the outcome you want will only serve to make you miserable. Focus on building small habits that get you closer to becoming a prolific writer. Soon enough, you will get there.

Lesson #2 Most negative comments will come from people who have never penned a single piece of data science content. Ignore them. Keep walking, and don't get distracted by people sitting on the sidewalks. Gather feedback from editors and other data science writers. Treat feedback as criticism of your work and not you.

Lesson #3 You don’t have to get every job you apply for. You can be a good fit for every company on the planet. Try and learn from every rejection but move quickly past it. The more data science writing work you do, the better you become. The more writing jobs you apply for, the more you learn about what companies are looking for. Getting rejected hurts. Learn and move quickly to the next opportunity. You can't win every battle. You just need to win some, and soon you will win more than you lose.

Learning these encouraged me to keep writing about data science and machine learning.

Writing about data science and machine learning can completely change your career's trajectory.

Writing technical content in data science is very different from other forms of writing.

In my new ebook, I distill my learnings from the last 5 years of creating data science and machine learning content while being paid.

Whether you want to write to get paid freelance work or full-time roles such as a technical writer or developer advocate, you will find the information invaluable.

Here are some benefits you can expect to get from the book:
💡 Benefit 1. Understand how to create data science technical content.
💡 Benefit 2. Learn how to generate and validate data science content ideas.
💡 Benefit 3. Discover where to find paid data science writing jobs.
💡 Benefit 4. Get your content to rank by implementing SEO best practices.
💡 Benefit 5. Understand how to promote your data science content

I'll also walk you through some case studies so that you can understand the end-to-end process of creating data science content.

Technical Writing

Derrick Mwiti Twitter

Google Developer Expert - Machine Learning


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