  As a result of the increased emphasis on mis- and over-use of $p$-values in
scientific research and the rise in popularity of Bayesian statistics, Bayesian
education is becoming more important at the undergraduate level. With the
advances in computing tools, Bayesian statistics is also becoming more
accessible for the undergraduates. This study focuses on analyzing Bayesian
courses for the undergraduates. We explored whether an undergraduate Bayesian
course is offered in our sample of 152 high-ranking research universities and
liberal arts colleges. For each identified Bayesian course, we examined how it
fits into the institution's undergraduate curricula, such as majors and
prerequisites. Through a series of course syllabi analyses, we explored the
topics covered and their popularity in these courses, and the adopted teaching
and learning tools, such as software. This paper presents our findings on the
current practices of teaching full Bayesian courses at the undergraduate level.
Based on our findings, we provide recommendations for programs that may
consider offering Bayesian courses to their students.
