Bayesian statistics offers an intuitive introduction to statistics and preparation for graduate school. However, beyond simple examples, computation is a barrier for many undergraduate students. In this talk we will discuss these challenges and suggest remedies. We will first identify the essential computational skills required to apply standard Bayesian methods in practice, and the skills typical undergraduate students possess. The discussion on bridging this gap will center around organizing course topics and classroom examples.