As data scientists, we rarely get asked LeetCode-style questions, so the need for us to learn data structures and algorithms is less than for software engineers.
However, being able to write efficient code is a great multiplier for your data science career. Imagine you can be a data scientist who knows how to implement ML models but also understands the best practices when it comes to writing code and has an appreciation and knowledge of software engineering?
You suddenly become very valuable and almost a unicorn in the market. That’s why I have started taking a data structures and algorithms course, from which I plan to share what I have learned.
This post will be dedicated to arrays, how they work under the hood, and their different types.
A data structure is a convenient way to store information inside a computer. As Wikipedia defines it:
A data structure is a data organization and storage format that is usually chosen for efficient access to data. More precisely, a data structure is a…