My advisor, Jarad Niemi, is posting lectures on Bayesian statistics on his youtube channel while teaching Stat 544 – the master’s/Ph.D. level introduction to Bayesian statistics at Iowa State University. I’ve taken a look at a few of them and they’re pretty good. Most are short (~10 minute) explanations of a particular topic in order to supplement required readings. Some of them, like the extended Metropolis within Gibbs example, are full lecture length, i.e. about one hour. Since the course is ongoing this semester, you can expect a few more to be posted.
The lectures do assume a rather high level understanding of probability theory. The statistics students in the class have seen at least chapters 1 – 5 of Casella and Berger in some detail. Other students in the class have similar backgrounds, though perhaps not quite as strong. Some knowledge of R would also be useful to understand the more computationally centered lectures. While the videos might not be useful for everyone, they’re probably a great supplement if you’re learning some of this material elsewhere.