Time and space complexity are terms used in computer science to analyze the efficiency of algorithms. Time Complexity measures the amount of time an algorithm takes to complete as a function of the input size. Space Complexity quantifies the amount of memory space an algorithm uses in relation to the input size.

Algorithms and Data Structures

LeetCode Solutions Time & Memory Complexity analyzer + Kazakhstan LeetCode community Support

[+] Data structures and algorithms is the most important topic in Computer Science. So, now learning for improving my problem solving skills also to become a better developer!

This repository is dedicated to studying and mastering Data Structures and Algorithms (DSA) using the Java programming language. It serves as a comprehensive resource for learning essential DSA concepts and their implementation in Java, covering everything from basic data structures to advanced algorithms.

Solving a Problem [less Time and Space complexity]

LeetCode solutions with Dart programming laungage, including explanations, A valuable resource for coding interview preparation and improving problem-solving skills with Dart.

A playground for practicing Data structure and Algorithm.

Program that simulates sorting arrays with multiple threads and different algorithms

My notes on EPAM Python Core course.

Computer Science Algorithms

This is a collection of the LeetCode problems I have solved

Java based fundamental concepts, data structures, and algorithms to solve coding problems effectively, with a focus on interview preparation.

Functions, concepts, and STL related to C++, Algorithms, Object-Oriented Programming, Memory allocation, etc.

9 Fibonacci Algorithms

This Repository contain Data Structure and Algorthims related material, problems and their solution in Java Programming Language

Python solution which uses min-heap data structure and thread parallalism to process very large file

Daily Coding Challenges from codewars.com to sharpen problem solving skills.

This repository provides a comprehensive roadmap for learning Data Structures and Algorithms (DSA)📊 from the ground up. It covers essential topics required for ☉ competitive programming, 📗 technical interviews, and real-world ✔ software development.

Code samples for Big O notation, Data Structures and Algorithms that constitute the basics of understanding coding principles.