42 Steps to Mastering Data Science

If you are interested in meta-tutorials on a variety of data science topics, you have come to the right place. Of the six 7-step tutorials included herein, the first 3 tutorials cover, in order, the machine learning process from data preparation through to several different types of machine learning tasks, including both theoretical understanding and practical implementation using Python libraries. The fourth tutorial covers deep learning, mainly from an "understanding" perspective, while the final 2 cover database topics: SQL for data science, and understanding NoSQL databases. And so with a nod to Douglas Adams, and the answer to life, universe, and everything, let's have a look at 42 steps to mastering data science. Whatever term you choose, they refer to a roughly related set of pre-modeling data activities in the machine learning, data mining, and data science communities.