This video is a summary of a course on OpenBUGS. The course starts with a motivation and a summary of Bayesian methods including the most important concepts, such as the basic moel, prior and posterior distributions, conjugate families, samples, and prior and posterior predictive distributions, which are illustrated with some examples. Next we explain how to use the Doodle tool to build the Bayesian network of the Bayesian model, which includes the model variables and also the model parameters. Next some examples of applications are discussed, such as the BPR travel time model, the parabolic regression model, the rate and the Pearson correlation model, etc. It is breafly explained how to work with scripts and use JAGS and matlab. Complete examples with the corresponding matlab codes are given for the readers to benefit from them and use them as starting work material to solve their problems.