Introduction to Data Structures and Algorithms

What is Data Structures and Algorithms?

Data Structures refer to the way we organize and store data in a computer so that it can be accessed and modified efficiently. Common examples include arrays, linked lists, stacks, queues, trees, and graphs. Each structure has its strengths and weaknesses, making them suitable for different tasks.

Algorithms are step-by-step procedures or formulas for solving problems. They are the logic behind how we manipulate data within these structures. Examples of algorithms include sorting algorithms like QuickSort and MergeSort, searching algorithms like Binary Search, and graph traversal algorithms like Depth-First Search (DFS) and Breadth-First Search (BFS).

Why Are They Important?

Understanding data structures and algorithms is crucial because they form the backbone of efficient programming. Whether you are optimizing code, reducing runtime, or managing complex data, a solid grasp of these concepts enables you to write code that is not only correct but also efficient and scalable. In real-world applications, this knowledge directly impacts the performance and resource usage of software systems.

About This Handbook

This handbook will serve as a supplementary learning resource for our Data Structures and Algorithms course. Here, you will find a collection of learning materials including links, tasks, projects, notes, and summaries that are designed to reinforce and extend what we cover in class.

Use this handbook as a guide to deepen your understanding, practice concepts, and explore additional topics that we may not have time to cover in detail during lectures. It’s a living document, so check back regularly for updates and new content.