Compilation of resources and insights that helped me on my journey to Data Scientist
Data science can seem like an intimidating field to get into. I know this first hand. Throughout my journey, I've failed more times than I've succeeded, but I've learned a lot. I've also documented a lot. Through this exciting and difficult process, I’ve accumulated a plethora of useful resources that helped me with learning new concepts, doing impactful work, interviewing at top tech companies, and more. This repo is an attempt to ‘open-source’ my experience and insights becoming a Data Scientist. Enjoy!
This list is a compilation of over 200+ undergraduate intern roles from Summer 2018 that were explicitly centered around data science and software engineering. Use this as a jumping off point for your next job search.
With this by your side, you should have more than enough effective tools at your disposal next time you’re prepping for a big interview or just suring up fundamental data science concepts. Being updated and improved on constantly.
Learn how to implement 8 fundamental machine learning algorithms in Python over the course of 8 minutes or less by leveraging the power of scikit-learn and Python for data science.
If you’ve ever found yourself looking up the same question, concept, or syntax over and over again when programming, you’re not alone. Here’s the stuff that I’m always forgetting when working with Python, NumPy, and Pandas.
Think of your newsletter subscriptions as an elite force of smart, specialized people working to bring you the latest and most valuable information well worth your time. Data science moves fast, you should too.
Data science isn't entirely about machine learning. Here I make the argument for the value provided by skills and actions associated with the often overlooked and under-appreciated, Type A Data Scientist.
As Data Scientists, there is very little that is black and white. We do our work in a world of grey. As Data Scientists, we need to do a better job of consistently reminding ourselves that our primary focus should be to drive impact.
This post is designed to help you achieve an edge in data science interviews by laying out a multi-step system to product knowledge and ideation that I’ve used with a lot of success.
Internships can be a tricky thing— both for managers and interns alike. This post touches on some common pain points and tips that I recommend for incoming data science interns or more generally, any interns.