Data Structure and Algorithms | Your Tech Salt

Examples for Calculation of Time and Space complexity

Let’s illustrate time and space complexity with some examples in Python. We’ll cover constant time, linear time, and quadratic time complexities. These examples will help you understand how to calculate the complexity of a program. Debdatta SarkarDebdatta has more than 13 years in IT induustry and software engineering. Currently 6 years in data science, and machine learning. She holds a Master of Computer Applications degree and Executive Post Graduate Program Degree in Data Science. She is passionate about research, data-driven decisions, and technology’s role in business growth.

Classification within DSA?

Data Structures and Algorithms (DSA) is a broad field that can be categorized in several ways. Here’s an overview of the different categories: 1.Data Structures Primitive Data Structures Integers Floats Characters Booleans Non-Primitive Data Structures Linear Data Structures: Debdatta SarkarDebdatta has more than 13 years in IT induustry and software engineering. Currently 6 years in data science, and machine learning. She holds a Master of Computer Applications degree and Executive Post Graduate Program Degree in Data Science. She is passionate about research, data-driven decisions, and technology’s role in business growth.

What is DSA and why its important?

Data Structures and Algorithms (DSA) form the cornerstone of computer science and software development. They are critical tools that allow programmers to solve complex problems efficiently and effectively. Understanding DSA is essential for anyone looking to pursue a career in technology, as it provides the foundation for writing optimal code and developing robust applications. Debdatta SarkarDebdatta has more than 13 years in IT induustry and software engineering. Currently 6 years in data science, and machine learning. She holds a Master of Computer Applications degree and Executive Post Graduate Program Degree in Data Science. She is passionate about research, data-driven decisions, and technology’s role in business growth.