There are a plethora of data science resources out there for your disposal, and they all will claim to be the “best possible introductory to advanced material and courseware on the subject of data science.” It is important that you make sure you to pick the right resources if you want to broaden your knowledge on a subject as dense and complex as data science. These resources can be through books, electronic books, websites, etc. With that said, here are some of the must-have resources in order to become a data scientist.
This is one of the best books you can use if you want to become a professional data scientist. It was written by an authority who has over fifteen years of experience in the industry and is working on some very large-scale projects for some of the top companies in the world. This book contains some of the most up to date and best methods you will need to become a professional data scientist. Plus, it doesn’t just include teaching theory as every chapter includes case studies taken from real-life experiences within the industry. The level of this book is pretty advanced and not recommended for beginners. However, for those intermediate-advanced data scientists, this book will be perfect for helping you reach the next level within your career.
R for Data Scientist (Book)
This is a great book for beginners as it teaches all the basics of R for the people who have basic programming skills. R or R Studio is a language intended for the manipulation of raw data making it an excellent asset to your toolbox, especially if you already know Python and are preparing for a career in data science. Both of the authors or this book are chief data scientists involved in the RStudio software development team and are members of the R Foundation as well.
There was once a time when a developer who was stuck on a particular programming problem had to sift through several textbooks to find the answer to their problem. That is no longer the case with StackOverflow. This website is a platform for questions and doubts on almost every type of programming language available including Python, R, Keras, Pytorch, etc. It involves the power of crowdsourcing problems making it much easier to find the answer to a problem. You simply copy and paste your error message in the data science compiler tool, and the site will return fully worked and explained answers to that problem.