RESOURCES -

Data Science Blogs

Towards Data Science — Towards Data Science is a Medium content aggregator of written content related to data science and machine learning, including tutorials, news, and career tips.
Dataquest Blog — Our data science blog has helpful tips, tutorials, other resources on the fields of data science, data analytics, and data engineering.
Data.world blog — Data.world a great source for user-supplied data sets, but the site also has a useful blog with interviews with industry figures, tips, and other great content.
FiveThirtyEight — FiveThirtyEight uses statistical analysis — hard numbers — to tell compelling stories about elections, politics, sports, science, economics, and lifestyle. If you want to see what really compelling data storytelling looks like, this is a great source.
Priceonomics — Priceonomics uses business data to tell stories, which is a skill any professional data scientist or data analyst needs. This blog provides a great source of inspiration.
Information is Beautiful — Information is Beautiful is a blog dedicated to posting incredibly well-designed data visualizations in the form of charts and infographics. If you aspire to improve your data visualization skills, their work is absolutely worth studying.
R Bloggers — An aggregator/syndicator of great R content from all over the web.
R Weekly — A weekly curated list of great R-related content

Hacker Rank — Practice your coding skills to prepare for technical interviews.
HackerEarth — Participate in programming challenges, and improve your programming skills. We’re currently running a HackerEarth challenge you can sign up for right here.
Kaggle — Participate in data science challenges to hone your data science skills and constantly improve them.

Data Science Career Guide — An exhaustive seven-part guide to navigating the data science job hunt, from how to start your search all the way through how to negotiate a great salary.
The Muse — The Must publishes career advice articles on topics from designing your resume and cover letter to finding the best positions for your skill set.
Glassdoor — Glassdoor allows you to look up how past and current employees view a company, look up salary data for a company, and see potential interview questions.
Indeed — Indeed is a giant job board, but they also have searchable data resources on career-related topics like salaries. It’s a great place to look up, for example, what the average data scientist makes in your city.
G2Crowd — Crowd reviews of many data science learning platforms as well as data science software solutions. They also have a learning hub that contains some good career advice.

PyCon — PyCon hosts several Python conferences each year in multiple countries.
PyData — PyData is an educational program of NumFOCUS, a nonprofit charity promoting the use of accessible and reproducible computing in science and technology.

Best Free Books for Learning Data Science — A blog post written by us that aggregates the best free books to learn data science.
Deep Learning — This textbook is designed to help machine learning practitioners get familiar with deep learning.
Natural Language Processing in Python — If you have an interest in NLP, this book is highly recommended for you to check out. This book is written to give you an overview of the NLTK library.
Intro to Statistics — This book is designed to give you a traditional introduction to statistics at the college level.
Hands On Machine Learning — Interested in Machine Learning and with a more “hands-on” approach? This book is a great introduction if you are new to machine learning or just want a refresher.
Think Stats — A book that will walk you through how to think about statistics as you program in Python or R.