Foundations of Data Structures: Essential Concepts for Data Science Coding Interviews [Part 2]

Data Structure Basics for Data Science Coding Interview

In the dynamic field of data science, proficiency in fundamental data structures is crucial, especially for excelling in coding interviews. This initial installment of a comprehensive series explores essential data structure concepts vital for aspiring data scientists.

From foundational structures like arrays and linked lists to more intricate ones such as trees and graphs, each section provides insights to cultivate a holistic understanding. 

Mastering these structures not only showcases problem-solving skills but also offers a strategic advantage in algorithmic thinking during data science interviews.

This second part will delve into advanced topics like dynamic programming and disjoint sets (union-find), aiming to empower enthusiasts with the knowledge needed to navigate complex coding interviews.

Table of Contents:

1. Arrays [Covered in Part 1]

2. Linked Lists [Covered in Part 1]

3. Stacks [Covered in Part 1]

4. Queues [Covered in Part 1]

5. Trees [Covered in Part 1]

6. Graphs [Covered in Part 1] 

7. Hashing

8. Heaps

9. Trie

10. Sets and Maps

11. Dynamic Programming

12. Disjoint Set (Union-Find)

---