This short lesson summarizes the topics we covered in section 07 and why they'll be important to you as a data scientist.

You will be able to:

• Understand and explain what was covered in this section
• Understand and explain why this section will help you become a data scientist

We spent a lot more time in this section deepening both our knowledge of and experience of working with Object Oriented Programming concepts. Key takeaways include:

• Objects can be really useful for using software to model real world entities like companies, customers and orders
• Objects have both state (properties) and behavior (methods - functions associated to an object)
• Classes can also have state (class variables/properties) and behavior (class methods)
• Inheritance is a powerful way to reuse code by allowing (for example) a Vendor and a Customer to share properties and methods by extending from the same Company class
• Inheritance can be overused - think about "is a" vs. "has a" and favor composition over inheritance

And after our deep dive into OOP, let's get back to the data science. In the next section we'll be learning about NumPy and the foundations of probability and combinatorics!