By Nate Rosidi, Data Scientist & Product Manager
Photo by JESHOOTS.COM on Unsplash
If you want to have a career in data science, knowing Python is a must. Python is the most popular programming language in data science, especially when it comes to machine learning and artificial intelligence.
To help you in your data science career, I’ve prepared the main Python concepts tested in the data science interview. Later on, I will discuss two main interview question types that cover those concepts you’re required to know as a data scientist. I’ll also show you several example questions and give you solutions to push you in the right direction.
Technical Concepts of Python Interview Questions
This guide is not company-specific. So if you have some data science interviews lined up, I strongly advise you to use this guide as a starting point of what might come up in the interview. Additionally, you should also try to find some company-specific questions and try to solve them too. Knowing general concepts and practicing them on real-life questions is a winning combination.
I’ll not bother you with theoretical questions. They can come up in the interview, but they too cover the technical concepts found in the coding questions. After all, if you know how to use the concepts I’ll be talking about, you probably know to explain them too.
Technical Python concepts tested in the data science job interviews are:
- Data types
- Built-in data structures
- User-defined data structures
- Built-in functions
- Loops and conditionals
- External libraries (Pandas)
1. Data Types
Data types are the concept you should be familiar with. This means you should know the most commonly used data types in Python, the difference between them, when and how to use them. Those are data-types such as integers (int), floats (float), complex (complex), strings (str), booleans (bool), null values (None).
2. Built-in Data Structures
These are list, dictionary, tuple, and sets. Knowing these four built-in data structures will help you organize and store data in a way that will allow easier access and modifications.
3. User-defined Data Structures
On top of using the built-in data structures, you should also be able to define and use some of the user-defined data structures. These are arrays, stack, queue, trees, linked lists, graphs, HashMaps.
4. Built-in Functions
Python has over 60 built-in functions. You don’t need to know them all while, of course, it’s…
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