This course mainly includes the introduction of various intelligent computation techniques (Decision Tree Learning, Association Rule Learning, Clustering, Support Vector Machine, Bayesian Networks, Reinforcement Learning, Genetic Algorithms, Genetic Programming, Neural Networks, Ant Colony Optimization, Particle Swarm optimization, various methods in Deep Learning etc) and how to use them to solve problems in different domains. GA and GP parts involve how to define a genetic representation for a problem to be solved, and then apply the evolutionary techniques, such as reproduction, recombination and mutation to produce solutions which suit the problem the most. Different kinds of Neural Networks, such as feed-forward, recurrent, and Hopfield nets, and their corresponding training methods will also be introduced in this course. In addition, Ant Colony Optimization, Particle Swarm optimization, various methods in Deep Learning will be introduced and applied to numerous applications, particularly for image processing, cloud computing and big data.