Fundamental Concepts of Probability (i.e., Set Operation, Sample Space, Events and Probabilities, Probability Axioms, Conditional Probability, Independence, and Bayes’ Theorem), Discrete Random Variables (i.e., Bernoulli, Geometric, Binomial, and Poisson Random Variable), Continuous Random Variables (i.e., Uniform, Gaussian, and Standard Normal Random Variables), probability density function, probability distribution function, Expectation and Moments of a random variable, Characteristic function, Expectation of random vectors, Central limit theorem, Markov Chains (i.e., Definitions and properties, Discrete time Markov chains, Continuous time Markov chains).