Notes of Algorithms Learning

This repository contains all the solutions of assignments, starter files and other materials related to this specialization.

Algorithms-Specialization from Stanford:

🧙🏾‍♂️ Complex Algorithms and Complexity Course from the University of San Diego

Homeworks done in course CS 599: Algorithms - Design, Analysis, and Implementations at Oregon State University

Coursera Data Structures and Algorithms Specialization course 5 --> Advanced Algorithms and Complexity... Code is completed in python only.

Strip Packing Written in C++

This repo contains the implementation of an heuristic to solve the Traveling Tournament Problem (TTP), as well as the implementation of the Meta-heuristics' algorithm Iterated Local Search (ILS) satisfying the predefined contraints of the NP-hard problem.

What I learned from Data Structures and Algorithms Specialization on Coursera.

Non-Deterministic Objects library (CombView API)

Algorithm Analysis and Development

Strategies for solving a power system network planning problem through greedy strategies, using dynamic programming and flow approximation algorithms. NP-Completeness analysis. The Min K-Cut problem

Presents a reduction from 3DM to Nonogram

An 8086 assembly quiz game on computational complexity, featuring user authentication, randomized MCQs, case-insensitive input, a 12-second timer, and a leaderboard. Built with BIOS interrupts and modular code, runs on 8086 emulators.

Foundations of Computer Science

An implementation of an A* Informed Search Algorithm for solving the N-Puzzle problem, using several heuristic functions, written in C

The aim of the course is to provide a solid knowledge on how to design and analyse the most important classes of algorithms.

Repositório da cadeira de Análise e Projeto de Algoritmos

All the Programs of the 5th Sem Analysis of Algorithms Lab with their output in different steps. This lab provides students with hands-on experience in implementing, analyzing, and comparing fundamental algorithms. It focuses on practical exposure to algorithm design techniques such as divide and conquer, greedy methods, dynamic programming etc.

Course projects on various NP and NPH problems on CTU in Prague 2021. Knapsack problem with various approaches, analysis of effectivity and robustness. Instances generation and validation. Approximation algorithms (FPTAS) and advanced iterative methods (genetic algorithm, simulated annealing).