Data Science
Learning Data science is a journey in itself. And a mighty hard one at that. So much to learn and so many paths to choose that it leaves us confused at times. I get many questions regarding how I learned Data Science? Or which books I find good? So I thought of adding the resources I found useful to this page. As you may understand, this is an ever increasing list so it might help to bookmark this page.

Books For Data Science

These books are some of the most important texts when it comes to Data Science. And something that should be in the bookshelves of every Data Scientist.
You just can't go wrong with any of these books.

Online Data Science Masters

Although you can find many resources for Data Science on the internet, sometimes having a degree helps as it provides one with structured learning. And a lot of people are looking to do a degree with their ongoing jobs.
I have not yet done a masters but these would be one of my choices if I were to do one.

Master of Data Science, HSE University

The first fully online Master of Data Science from a top-10 Russian university, featuring applied projects with industry partners like Yandex.

Master of Machine Learning and Data Science,Imperial College London

One of the world’s first online master’s in machine learning from a world-leading institution.

Master of Applied Data Science, University of Michigan

Learn from the #1 public research university in the U.S. and join the next generation of data scientists.

Online Courses

In his book, The Paradox of Choice — Why More Is Less, Schwartz argues that eliminating consumer choices can greatly reduce anxiety for shoppers. And the same remains true for Data Science courses as well. So here are the courses that I found are the best when it comes to Data Science. Do take a look at this post also for more information about these courses.

Data Science



Deep Learning

Data Structures and Programming


As you all know I write beginner friendly Data Science posts. Follow me up at Medium or Subscribe to my blog below to be informed about them. As always, I welcome feedback and constructive criticism and can be reached on Twitter @mlwhiz. Also do share this page on your social as sharing is caring.