Prepare for the actuarial probability exam with this comprehensive 11-hour course covering essential topics in probability theory. Learn set theory basics, sample spaces, events, Kolmogorov axioms, counting techniques, conditional probability, and multiplication law. Explore independent events, total probability law, Bayes' rule, random variables, discrete and continuous distributions, expectation, variance, and moment-generating functions. Study specific probability distributions including Bernoulli, binomial, geometric, negative binomial, hypergeometric, Poisson, exponential, gamma, uniform, normal, beta, and chi-squared. Delve into Markov's and Chebyshev's inequalities, and conclude with an introduction to multivariate probability distributions, joint probability mass functions, and probability density functions.