- Why learn DSA?
- Importance of structuring data
- What is a data structure?
- Classification of data structures
- Algorithms
- Prerequisites
Learning DSA is essential for any programmer who wants to improve their problem-solving skills, write efficient code, and increase their chances of getting placed in top companies.
Structuring data efficiently allows for faster access and manipulation. It reduces time and space complexity in algorithms, making code more efficient.
A data structure is a particular way of storing and organizing data in a computer for efficient use.
Data structures can be linear or non-linear:
- Linear data structures: Arrays, linked lists, stacks, queues, etc.
- Non-Linear data structures: Trees, graphs, etc.
Algorithms are step-by-step logical representations to solve problems efficiently.
To start with DSA using Python, you should have:
- Basic understanding of Python
- Knowledge of built-in types, control statements, functions, classes and objects
Stay tuned for updates and tutorials in this series!
This repository is licensed under the BSD 3-Clause License. See the [BSD 2-Clause License](Copyright (c) 2024, Vikas Kumar) file for details.
In addition to the topics mentioned above, this repository includes:
- Implementation examples of various data structures and algorithms in Python.
- Practical exercises to reinforce learning.
- Tips and tricks for optimizing code performance.
- Supplementary resources such as articles, videos, and further reading materials.
Feel free to explore the repository and contribute to enhance your understanding of Data Structures and Algorithms using Python!
In this version, I've added a BSD 3-Clause License section and mentioned additional content that could be included in the GitHub repository, such as implementation examples, exercises, tips, tricks, and supplementary resources.