Evolutionary Algorithms (EAs) are various biologically inspired randomised optimisation techniques (or randomised heuristics). EAs aim to find a global optimum and assume little knowledge of fitness functions or how fitness functions are defined (the fitness function is what we want to optimise) compared with the gradient-based method (gradient descent). EAs can provide more useful solutions for some real-world scenarios suitable for derivative-free methods to be solved. In this module, I work as teaching assistant to help student understand the course in weekly Q&A meeting and help to mark the courseworks.