An important part of being a professional data scientist is being able to communicate clearly - both in writing and in person. Because of that, we will be asking you to write at least seven blog posts before graduating. This short lesson provides a little more information about why we ask you to blog, what we ask you to blog about, and how we'd like you to blog.
As a professional data scientist, you'll often have to communicate in writing. Sometimes you'll have to write something technical for your peers, at other times you'll have to provide a non-technical summary for business stakeholders. In either case, it's important to be able to distill a complex technical topic and share in writing the most important points.
A blog can also help you to get a data science job. It's a way to showcase your skills to potential employers before they decide to interview you, so it's important to realize that your blog posts may well be reviewed by potential employers when deciding whether or not to grant you an interview.
Think about blogging through the following lenses:
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Your blog is for you. Writing a blog gives you an opportunity to solidify knowledge or gain depth of understanding. Your ability to communicate about your work, both verbally and in writing, is essential for success as a data scientist. Blogging is a great way to reflect on your work and helps you consolidate everything you've learned and decide how you want to grow next.
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Your blog is for your peers. At some point in the program you will find a peer's blog to be helpful or inspiring. You can be that person for someone else!
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Your blog is for the larger community. As you go through the course you will be googling for things and find blog posts that others have written that will be immensely helpful to you. It may not feel like it, but you already know enough to contribute back to the community. If the blog post you are writing would have helped you last week, someone else will find it useful and valuable.
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Your blog is for potential employers. Your blog posts can be an additional bullet point to add to your resume and a way to establish your presence and credibility. Student blogs have been picked up by Medium publications and students have even become exempt from technical interviews due to knowledge they demonstrated in a blogpost!
There are seven blog posts that we'll ask you to complete. These blogs are required in order to graduate! Note: On-campus students may have different requirements, please speak with your instructor. Please feel free to write more posts, although in general a "reasonable quantity and great quality" is probably the best strategy so you can have 1-2 posts that you can point potential employers to that really show how you can write for both technical and non-technical audiences. The risk of too many posts is that employers will click onto some of the weaker ones if you didn't have the time to make them all great.
Here are some suggested blog topics:
- Why did you decide to learn data science?
- Write a post on a visualization technique of your choice (line plot, histogram, heat-map, etc). How is it being used to answer analytical problems and what are it’s strengths and weaknesses?
- Something you learned when building the Mod 1 Project. Exploratory Data Analysis, feature selection, choice of visualizations.
- Statistical analysis and hypothesis testing (Mod 3).
- Time-Series Modeling and Analysis (Mod 4).
- Building and interpreting a classification model (Mod 5).
- A breakdown of any of the larger end-of-Mod projects where you explain your problem and the dataset along with your process, methodology, and findings.
- Solidify knowledge. Write about a topic you are finding particularly challenging. Do it in the form of a tutorial to help another aspiring data scientist to learn that topic.
- Go Deeper. Write a tutorial (with a data set and code sample) on something that we did not cover during the course that you think might be interesting to other people taking the course. It can be a topic we didn’t cover at all, or can just go deeper into a topic that we did cover.
- Pick a data science paper written in the last 18 months and rewrite it to explain it to a non-technical business stakeholder. Focus on why it’s important and why it would matter to them.
- Pick one of the most influential papers in the history of data science (ask us for a list!) and rewrite it to explain it to a non-technical business stakeholder. Focus on why it’s influential and why it would matter to them.
In terms of length, there isn't a set requirement. Strike a balance between providing a meaningful and worthwhile investigation of your topic and being concise and focused. It's a blog post -- not a novel, so you might want to constrain the scope so it can be fitted into (say) 1000-3000 words (yes, 3500 words is fine if you need it!)
When presenting code, use code snippets instead of screenshots. This will allow others to copy and paste your code if following along with your post.
Provide links to resources you used to help you write your post and give your readers more context.
If you already have a blog for work related topics, feel free just to add your posts to that. If you have a personal blog, you might want to set up a separate "work" blog. It's not required, but do consider that employers will probably look at multiple posts from any blog you share, so if you mix personal and business postings, make sure they're equally high quality and would reflect well on you when being considered for a job. Finally, if you've never blogged before, not to worry! Pick your favorite blogging site/software and start blogging. Don't worry too much about which platform you pick - just pick something and focus on writing great content.