This graduate course  covered the essentials of Linear Systems (Laplace and Z‐transforms, stability, impulse response, transfer functions, and state‐space models, in continuous‐time and discrete‐time); Applied probability and statistics (recap. of elementary concepts, regression, central limit theorem, goodness of fit test); Optimization (unconstrained optimization, constrained optimization with equality and inequality constraints, and linear programming).