This repository contains the projects and materials developed during the "AI and Meta-Heuristics (Combinatorial Optimization) Python" course from Udemy.

Graph Algorithms, Genetic Algorithms, Simulated Annealing, Swarm Intelligence, Heuristics, Minimax, and Meta-Heuristics. The course covers:

1. Understanding Artificial Intelligence

   • Learn why artificial intelligence is important.

2. Pathfinding Algorithms

   • Understand BFS, DFS, and A* search algorithms for pathfinding.

3. Heuristics and Meta-Heuristics

   • Learn about heuristics and meta-heuristics.

4. Genetic Algorithms

   • Understand genetic algorithms for optimization.

5. Particle Swarm Optimization

   • Learn particle swarm optimization techniques.

6. Simulated Annealing

   • Understand the simulated annealing algorithm for optimization.

The repository is organized into sections, each reflecting different topics and projects from the course.

• Python

Udemy Course: AI and Meta-Heuristics (Combinatorial Optimization) Python