This is the second in a series of posts on how to build a Data Science Portfolio. If you like this and want to know when the next post in the series is released, you can subscribe at the bottom of the page.
You can read the first post in this series here: Building a data science portfolio: Storytelling with data.
Blogging can be a fantastic way to demonstrate your skills, learn topics in more depth, and build an audience. There are quite a few examples of data science and programming blogs that have helped their authors land jobs or make important connections. Blogging is one of the most important things that any aspiring programmer or data scientist should be doing on a regular basis.
Unfortunately, one very arbitrary barrier to blogging can be knowing how to setup a blog in the first place. In this post, we’ll cover how to create a blog using Python, how to create posts using Jupyter notebook, and how to deploy the blog live using Github Pages. After reading this post, you’ll be able to create your own data science blog, and author posts in a familiar and simple interface.
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