*What is a Data Structure?* A data structure is a way of organizing and storing data so it can be accessed and worked with efficiently. If algorithms are recipes, then data structures are the containers that hold the ingredients — each designed for a specific purpose. *Why Do We Need Data Structures?* - To store data in a meaningful way - To perform operations like search, insert, delete quickly - To optimize performance in coding interviews and real-world apps *Types of Data Structures:* Here are some common ones you’ll master in this series: - Array: A collection of items stored in a contiguous block of memory. Used when the number of elements is fixed and you need fast access by index. - List: A collection that can store elements in any order and allows dynamic resizing (more flexible than arrays). Python lists are a great example. - Stack: A collection of elements where you can only add or remove elements from the top (LIFO – Last In, First Out). - Queue: A collection where elements are added at the back and removed from the front (FIFO – First In, First Out). - Linked List: A collection of nodes where each node points to the next one. Great for dynamic memory allocation and efficient insertions/deletions. - HashMap (or Hash Table): Stores data in key-value pairs, allowing for fast lookups by key. - Tree: A hierarchical structure where data is stored in nodes connected by edges, useful for representing hierarchical data like file systems. - Graph: A collection of nodes (vertices) and edges that represent relationships, often used for networks and paths. Data structures are a key part of coding interviews. The right data structure for the task can make your code more efficient in terms of speed and memory, which is what interviewers are looking for when they ask you to solve problems.