WELCOME

Chances are you’ve navigated to this blog from either my resume, it’s not that deep, or you dove incredibly far into the depths of the web. In the future, that’ll change but for now, I’m glad you’re here.
Why start a data science blog?
I’m really passionate about creating content and communicating highly technical concepts to nontechnical audiences. Unfortunately, as I’m entering my fourth year as an undergrad, I’ve found that there’s minimal accessibility to data science at Rutgers: there are virtually no quality organizations, and any data science courses available are either in the graduate schools or are junior/senior-level courses.
Likewise, a number of my friends in nontechnical degrees have expressed their interests in data science, while simultaneously complaining about how they’re incredibly overwhelmed with the wealth and breadth of information that exists.
And, most/least importantly depending on whom you ask, I’m starting this blog to help myself! I consider myself a fan of, but not yet an expert in, data science and I want to be able to document my trials and tribulations in bridging that gap.
My hope is that in creating this blog, I can provide myself with a deeply thorough understanding of the intricacies of the data science life cycle while also offering others my synthesis of the data science courses/tracks out there. Specifically, I want to:
- Create highly abstract-able approach to data science that people can use as “templates” when dealing with their various projects
- Demystify technology and programming for those with nontechnical backgrounds
- Help those around me double down on their passions with the help of data science
What to expect
While the inspiration for this blog was from the people around me, this is also a medium (ha, ha, ha) for me to really understand what data science has to offer. As such, there will be articles of varying complexities (think: “Your First Data Visualization” to“Creating a Multi-Class Classifier for Political Sentiment”). Don’t worry: these disparate articles will be placed in themed tabs, and won’t exist in the same context.
This blog will be a tour of data through R, Python, and SQL primarily. I’ve chosen these three languages because R and Python are the hottest languages . To that effect, every post will include guidance in both of the languages. SQL is thrown in the mix because querying data is just as important as analyzing data!
Warning: a lot of the instruction given throughout the blog will be specific to Mac users — as I have a Mac, and no PC to test the steps of my projects, it’s hard for me to give accurate information. However, I will be providing links for Windows users for any information that is platform/OS-dependent.
Expect there to be a “TLDR” section for each post, in which there’s a bulleted overview of the article and a practical guide to approach the given problem. Think of this as your “template” to take away for the future!
I’m really really really excited to start this journey, and I’m privileged to have you even read my words.
To Ashleigh, Steven, and Sachit, y’all are the MVPS for the inspiration.
Welcome to my data science blog ✌🏽

