A data structure organizes data to be used efficiently by computer programs. Algorithmic notation like Big-O describes the performance of algorithms as the input size increases. Common notations include O(n) for linear time, Ω(n) for linear lower bound, and Θ(n) for tight linear bounds.

GitHub - TZhoroev/Coursera-Data_Structures_and_Algorithms: This repository is a compilation of my solutions to the Data Structures and Algorithms assignments offered by the University of California, San Diego (UCSD) and the National Research University Higher School of Economics (HSE) on Coursera.

This section provides the problem sets assigned for the course, solutions, and assignment policies.

Completed 4 out of 6 courses of Data Structures and Algorithms Specialization by University of California San Diego. This repository contains my solutions for the assignments of the four courses. The language I used in the solutions is C++.

These assignments cover practical implementations and theoretical concepts, including algorithm analysis, growth rates, custom data structures, P vs NP problems, efficient data retrieval, and graph data structures. The repository includes documentation and is primarily written in Python.

Download now thousands of Assignments in Data Structures and Algorithms on Docsity.

Data Structure #1: Linked List! • Data structure: Nodes; each contains key/value pair and pointer to next node! • Algorithms:! • Create: Allocate Table structure to point to first node! • Add: Insert new node at front of list! • Search: Linear search through the list! • Free: Free nodes while traversing; free Table structure!