Most of the tutorials are self sufficient. But you should have some knowledge of Python to understand some project based tutorials like Predicting Titanic Survivors with Machine Learning.
It depends on your need. For example if you want to use cutting edge statistical methods , R is a better options while Python is better when you want to build a scalable product. These articles will help you understand it better:
Hello Shaurya, you can use the notebook along the tutorial. The best way to learn is by doing. Play with the note book, learn what those code is doing from the tutorial , post questions if you find any portion difficult to follow. In that way you will get best out of this tutorial :)
Feature bucketing is a feature engineering technique in which we convert continuous values of some feature ( for example age) to fixed ranges ( like 10-15, 15-20). This technique proves helpful in reducing noise endured by machine learning algorithms resulting in enhanced performance. You can explore the idea further in this blog :