Understing Random Forest Classifier

Trying to understand the process of Machine learning and learning what decision trees are and how they work for this project. 
All code was from EmpowerCode : https://www.youtube.com/playlist?list=PLvICEeb-TZEHKkojcv1_POKPrCwlsEnsI [Building a Random Forest Classifier in Python]


Using a Jupyter Notebook, VS Code and Python to understand what first is a decision tree algorithm and how does it fit in with Machine learning. What are the 
advantages of using Decision trees algorithm? Understing the Machine learning process from start to finish. Learning what features are in Machine learning.
What features can be added to improve the Algorithm? These are some of the topic points that I will be learning with this project and will address on this project.