Optimization with Metaheuristics in Python

Overview

This advanced course explores metaheuristic optimization algorithms and their practical implementation using Python. Learners study techniques like genetic algorithms, simulated annealing, particle swarm optimization, and tabu search to solve complex optimization problems that traditional methods struggle with. The curriculum covers problem formulation, algorithm design, and performance evaluation. Hands-on coding assignments enable students to apply these methods to real-world scenarios such as scheduling, routing, and resource allocation. This course is ideal for data scientists, engineers, and researchers aiming to enhance problem-solving...