The Tools You Need to Take Your Data Science Learning and Career to the Next Level
My resources section is a curated list of the tools and websites I strongly recommend for learning analytics and building a data science career. I have tested every recommendation on this page. Many of the resources listed here have been and continue to be crucial to my growth as a data scientist.
Before digging into these awesome resources, an important disclosure:
Some of the links below are affiliate links, which means that if you choose to make a purchase, I will earn a commission. This commission comes at no extra cost to you. I have experience with all of these companies and products, and I recommend them because they are helpful and useful, not because of the small commissions I make if you purchase something. Please do not spend any money on these products unless you feel you need them or that they will help you achieve your goals.
Companies to Help You Find a Great Job
As we all know, job searching can be a stressful and tiring experience. Luckily for us, data science and analytics are an in-demand fields, and there's a new type of company that can help you get a job with much less stress! Here's how it works:
- You fill out a quick application detailing your background and the types of jobs you're looking for.
- They will forward your information to companies looking for your talents. You can block your current employer from seeing this.
- The companies apply to you, complete with job position and salary expectation.
- You decide which companies you'd like to interview with!
In my most recent job search, I worked almost exclusively through these companies to find interesting opportunities. Two of my favorites:
Hired is a free service that makes your job application process easy. Their value proposition is in getting leading companies to apply to you! You get to choose which interviews you'd like to pursue. I had a great experience with Hired during my last job search, and it seems their data science and analytics offering has only improved since then. They help you with coaching, interview prep, and job market expertise along the way, so you know you're getting the best deal from your future employer. If you're in the market, you definitely want to check out Hired!
Indeed Prime is another free service that aims to make your job search as painless as possible. You fill out a 5-minute application, and they get to work finding great jobs that match your criteria. They help you prepare for interviews with a dedicated career coach, and they also provide negotiating tips to help you maximize your salary. Indeed Prime has a huge network of companies, and they can help you find positions in over 90 cities throughout the United States, Canada, and the U.K. If you're looking to secure a high-paying and exciting position, Indeed Prime is a great place to start!
Start a Blog To Supercharge Your Career
Creating my blog is, by far, the most profitable thing I have ever done for my career. I got my first data science job because of this blog. I'm able to help thousands of other people on their journeys to learn R and improve their careers each month because of this blog.
I can trace much of the money I've made and the career satisfaction I've enjoyed over the last 5 years directly to this blog.
Still, when I encourage other data scientists and analytics people to start a blog, they're skeptical.
I get it. A blog is a commitment. And you won't see success overnight. But I promise you this: if you start a blog and stick with it, writing consistently, you will see success. You will learn new things, grow your network, find new job opportunities and grow your income. Again, it won't happen overnight, but starting a blog is the single highest leverage thing you can do to grow your analytics career.
Bluehost is the service that I recommend for starting your blog. They make it extremely easy to get your site up and running with their one-click automatic WordPress Blog installation. The last thing you want when first starting your blog is to be drowning in technical issues. Bluehost is the simplest service that I've found to get your blog started.
In a culture increasingly driven by quick hits of information on social media sites like Twitter and Facebook, I am a strong believer in the value of focus. Focused reading of a single topic is still the best way to understand something deeply. I spend a good amount of my time reading every day, and I think that this makes me a better programmer, a more nuanced thinker, and a more well rounded person.
The books below are my top recommendations for learning R, statistics, and data visualization. I am also including books that I believe are good resources to help you interview, get a new job, and grow your career.
R for Data Science
Hadley Wickham and Garrett Grolemund
This is THE BOOK for learning how to use R for data science. This book is beginner-friendly and is suitable for readers with no prior programming experience. You will learn how to use R to turn raw data into insight, knowledge, and understanding. This book covers R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Read this book for a very good introduction to R so that you can start practicing data science as quickly as possible.
An Introduction to Statistical Learning
Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
This is my go-to book covering the array of statistical modeling techniques out there today. It starts from the basics of regression and builds toward more complex topics like support vector machines, tree-based methods, clustering, and more. This book gives you a framework for understanding how each model works in a way that is approachable, even for a beginner. Most importantly, each section comes with R code that you can use to practice working with and building models on your own.
Storytelling with Data
Cole Nussbaumer Knaflic
I have seen so many data scientists struggle to convey the information hidden in their data. They focus on the wrong things, share too much, and don't understand their audience. Is this you? We've all been there. Creating compelling presentations is about telling a story, and this doesn't come naturally. The lessons in this book will help you turn your data into high impact visual stories that stick with your audience.
The Visual Display of Quantitative Information
Edward R. Tufte
This is book is the bible of data visualization, still as relevant today as when it was first published. If you struggle with deciding which graphs to use and when to use them, this book is for you. If you struggle to get your work taken seriously, this is the book for you. If you want to differentiate yourself and your work from other analysts who simply can't be bothered, get this book.
Cracking the Coding Interview
Gayle Laakmann McDowell
This is the definitive book for whiteboard-style coding interviews. This book is marketed toward software developers, but it's just as relevant for data scientists. The fact is, you're going to get coding challenges in job interviews. The problems can be simple once you understand them, but will be incredibly difficult if you never practice. This book is an indispensable resource to prepare for and understand how to solve challenging algorithms and coding questions that are bound to come up in job interviews. I'm a big believer that you don't need to know everything to get a job as a data scientist. That said, you do still need to get through an interview in most cases, and this book will help get you there.
Top Data Science Podcasts
I'm also a big fan of listening to podcasts to learn about new material and keep up to date on the latest trends in data science. I listen to podcasts on the subway, when I'm walking around, or when I have an hour to kill with nothing to do. They're one of the best ways to get advice directly from experts in your industry.
You can check out my top 5 podcast recommendations below. But if 5 isn't enough, and you want more (trust me, I'm with you), then you'll want to check out my ultimate list of the top 41 data science podcasts that I recently created by crowdsourcing recommendations from Google search results. You can get the full list here:
Enrico Bertini and Moritz Stefaner discuss the latest developments in data analytics, visualization and related topics.
The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
The O'Reilly Data Show explores the opportunities and techniques driving big data, data science, and AI. Through interviews and analysis, they highlight the people putting data to work.
Roger Peng and Hilary Parker talk about the latest in data science and data analysis in academia and industry.
Your one-stop shop for essential data visualization and presentation skills for digital marketers, web analysts, and BI practitioners. This is the toolset you need to present your data, inform business decisions, inspire action, and become indispensable.