This course introduces the main concepts, techniques, algorithms and applications of evolutionary computation. Students will learn the core elements of evolutionary computation: representation, search operators and selection schemes. Search operators include different recombination/crossover operators and mutation operators (non-adaptive or adaptive mutation step-size and probability) for discrete and continuous search spaces. The students will learn how the recombination/crossover operators and mutation operators work individually or collaboratively for efficient search. Selection schemes covered include fitness proportional selection, ranking and tournament selection. Chromosome representations include both discrete and continuous cases. Constraint handling techniques will be covered. Other topics covered in this course include niching and speciation, co-evolution, multi-objective evolutionary optimisation, evolutionary learning, and theories. This course will also give students some practical experience on when evolutionary computation techniques are useful, how to use them in practice and how to implement them in different programming languages.