In this seminar I will present the Particle Swarm Optimization (PSO) and some of its applications. The Particle Swarm Optimization (PSO) method was introduced as an optimization method in 1995 (Eberhart and Kennedy, 1995). The PSO is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarms looking for the best solutions. PSO's foundation is based on the principle that each solution can be represented as a particle (agent) in a swarm. Each agent has a position and velocity vector and each position coordinate represents a parameter value. The PSO technique is an alternative method to solve global optimization problems is simpler and easy to handle. The PSO algorithm is applied for engineering and computer science optimization problems with constraints, like, optimal power flow (OPF), Data Cluster and Fuzzy Rules.