Dive into a comprehensive lecture series on Engineering Probability, delivered by Rich Radke at Rensselaer Polytechnic Institute. Explore fundamental concepts such as sample spaces, events, axioms of probability, and counting methods before progressing to more advanced topics including discrete and continuous random variables, probability density functions, and the Gaussian distribution. Learn about joint expectations, correlation, covariance, and delve into estimation techniques like Bayesian and maximum likelihood. Examine the Central Limit Theorem, hypothesis testing, and methods for generating random samples. This 22-hour course closely follows Alberto Leon-Garcia's textbook "Probability, Statistics, and Random Processes for Electrical Engineering" and provides a solid foundation in probability theory essential for engineering applications.